{"id":717,"date":"2024-05-22T15:56:52","date_gmt":"2024-05-22T07:56:52","guid":{"rendered":"https:\/\/www.hkubs.hku.hk\/eventsite\/iim-summer-workshop-2024\/?page_id=717"},"modified":"2024-05-24T10:53:57","modified_gmt":"2024-05-24T02:53:57","slug":"program","status":"publish","type":"page","link":"https:\/\/www.hkubs.hku.hk\/eventsite\/iim-summer-workshop-2024\/program\/","title":{"rendered":"Program"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-page\" data-elementor-id=\"717\" class=\"elementor elementor-717\">\n\t\t\t\t\t\t\t\t\t<section class=\"has_eae_slider elementor-section elementor-top-section elementor-element elementor-element-fda88ef elementor-section-full_width elementor-section-stretched elementor-section-height-default elementor-section-height-default\" data-id=\"fda88ef\" data-element_type=\"section\" data-settings=\"{&quot;stretch_section&quot;:&quot;section-stretched&quot;}\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-no\">\n\t\t\t\t\t<div class=\"has_eae_slider aux-parallax-section elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-1bc01fb\" data-id=\"1bc01fb\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-b9e6c6b elementor-widget elementor-widget-menu-anchor\" data-id=\"b9e6c6b\" data-element_type=\"widget\" data-widget_type=\"menu-anchor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.8.1 - 13-11-2022 *\/\nbody.elementor-page .elementor-widget-menu-anchor{margin-bottom:0}<\/style>\t\t<div id=\"about\" class=\"elementor-menu-anchor\"><\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"has_eae_slider elementor-section elementor-top-section elementor-element elementor-element-b3f7251 elementor-section-stretched elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"b3f7251\" data-element_type=\"section\" data-settings=\"{&quot;stretch_section&quot;:&quot;section-stretched&quot;,&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"has_eae_slider aux-parallax-section elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-1eb333c\" data-id=\"1eb333c\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-0325b9e elementor-widget elementor-widget-aux_modern_heading\" data-id=\"0325b9e\" data-element_type=\"widget\" data-widget_type=\"aux_modern_heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<section class=\"aux-widget-modern-heading\">\n            <div class=\"aux-widget-inner\"><h2 class=\"aux-modern-heading-primary\">\nWorkshop Program<\/h2><\/div>\n        <\/section>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"has_eae_slider elementor-section elementor-top-section elementor-element elementor-element-03255ff elementor-section-stretched elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"03255ff\" data-element_type=\"section\" data-settings=\"{&quot;stretch_section&quot;:&quot;section-stretched&quot;}\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"has_eae_slider aux-parallax-section elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-2ff86fc\" data-id=\"2ff86fc\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-3e152f4 elementor-widget elementor-widget-text-editor\" data-id=\"3e152f4\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.8.1 - 13-11-2022 *\/\n.elementor-widget-text-editor.elementor-drop-cap-view-stacked .elementor-drop-cap{background-color:#818a91;color:#fff}.elementor-widget-text-editor.elementor-drop-cap-view-framed .elementor-drop-cap{color:#818a91;border:3px solid;background-color:transparent}.elementor-widget-text-editor:not(.elementor-drop-cap-view-default) .elementor-drop-cap{margin-top:8px}.elementor-widget-text-editor:not(.elementor-drop-cap-view-default) .elementor-drop-cap-letter{width:1em;height:1em}.elementor-widget-text-editor .elementor-drop-cap{float:left;text-align:center;line-height:1;font-size:50px}.elementor-widget-text-editor .elementor-drop-cap-letter{display:inline-block}<\/style>\t\t\t\t<p>A PDF version of this page can be found\u00a0<a href=\"https:\/\/hkubs-stat.github.io\/HKU-2024-Summer-Workshop\/assets\/2024_Workshop_Program_HKUBS_Stat.pdf\">here<\/a>.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"has_eae_slider elementor-section elementor-top-section elementor-element elementor-element-8ebce7b elementor-section-stretched elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"8ebce7b\" data-element_type=\"section\" data-settings=\"{&quot;stretch_section&quot;:&quot;section-stretched&quot;,&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-no\">\n\t\t\t\t\t<div class=\"has_eae_slider aux-parallax-section elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-5d65ff9\" data-id=\"5d65ff9\" data-element_type=\"column\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-d578edc elementor-widget elementor-widget-aux_modern_heading\" data-id=\"d578edc\" data-element_type=\"widget\" data-widget_type=\"aux_modern_heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<section class=\"aux-widget-modern-heading\">\n            <div class=\"aux-widget-inner\"><h2 class=\"aux-modern-heading-primary\">\nMorning Sessions<\/h2><h3 class=\"aux-modern-heading-secondary\"><span class=\"aux-head-highlight\">Venue: CPD-3.28, Central Podium Levels \u2013 Three (CPD-3,\u00a0The Jockey Club Tower), Centennial Campus, HKU.<\/span><\/h3><\/div>\n        <\/section>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"has_eae_slider elementor-section elementor-top-section elementor-element elementor-element-8bb9b69 elementor-section-stretched elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"8bb9b69\" data-element_type=\"section\" data-settings=\"{&quot;stretch_section&quot;:&quot;section-stretched&quot;}\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-no\">\n\t\t\t\t\t<div class=\"has_eae_slider aux-parallax-section elementor-column elementor-col-33 elementor-top-column elementor-element elementor-element-aa66763\" data-id=\"aa66763\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-e43d2a3 elementor-widget__width-initial elementor-widget elementor-widget-text-editor\" data-id=\"e43d2a3\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p style=\"text-align: center;\">08:30-09:00<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"has_eae_slider aux-parallax-section elementor-column elementor-col-33 elementor-top-column elementor-element elementor-element-dd1bcf2\" data-id=\"dd1bcf2\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-1893f84 elementor-widget__width-initial elementor-widget elementor-widget-text-editor\" data-id=\"1893f84\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>Registration<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"has_eae_slider aux-parallax-section elementor-column elementor-col-33 elementor-top-column elementor-element elementor-element-a05798c\" data-id=\"a05798c\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-d778f7a elementor-widget__width-initial elementor-widget elementor-widget-text-editor\" data-id=\"d778f7a\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"has_eae_slider elementor-section elementor-top-section elementor-element elementor-element-a656427 elementor-section-stretched elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"a656427\" data-element_type=\"section\" data-settings=\"{&quot;stretch_section&quot;:&quot;section-stretched&quot;,&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-no\">\n\t\t\t\t\t<div class=\"has_eae_slider aux-parallax-section elementor-column elementor-col-33 elementor-top-column elementor-element elementor-element-2920497\" data-id=\"2920497\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-ca5adc8 elementor-widget__width-initial elementor-widget elementor-widget-text-editor\" data-id=\"ca5adc8\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p style=\"text-align: center;\">09:00-09:10<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"has_eae_slider aux-parallax-section elementor-column elementor-col-33 elementor-top-column elementor-element elementor-element-5676ff6\" data-id=\"5676ff6\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-751cc1d elementor-widget__width-initial elementor-widget elementor-widget-text-editor\" data-id=\"751cc1d\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>Opening: Haipeng Shen<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"has_eae_slider aux-parallax-section elementor-column elementor-col-33 elementor-top-column elementor-element elementor-element-226e440\" data-id=\"226e440\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-82f079a elementor-widget__width-initial elementor-widget elementor-widget-text-editor\" data-id=\"82f079a\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"has_eae_slider elementor-section elementor-top-section elementor-element elementor-element-0f09f57 elementor-section-stretched elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"0f09f57\" data-element_type=\"section\" data-settings=\"{&quot;stretch_section&quot;:&quot;section-stretched&quot;}\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-no\">\n\t\t\t\t\t<div class=\"has_eae_slider aux-parallax-section elementor-column elementor-col-50 elementor-top-column elementor-element elementor-element-cc21500\" data-id=\"cc21500\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-98e1e0b elementor-widget__width-initial elementor-widget elementor-widget-text-editor\" data-id=\"98e1e0b\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"has_eae_slider aux-parallax-section elementor-column elementor-col-50 elementor-top-column elementor-element elementor-element-b7a8a3c\" data-id=\"b7a8a3c\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-c3dda3d elementor-widget__width-initial elementor-widget elementor-widget-text-editor\" data-id=\"c3dda3d\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><strong>Session 1, Chair: Weichen Wang<\/strong><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"has_eae_slider elementor-section elementor-top-section elementor-element elementor-element-6b7d111 elementor-section-stretched elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"6b7d111\" data-element_type=\"section\" data-settings=\"{&quot;stretch_section&quot;:&quot;section-stretched&quot;,&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-no\">\n\t\t\t\t\t<div class=\"has_eae_slider aux-parallax-section elementor-column elementor-col-33 elementor-top-column elementor-element elementor-element-34feb10\" data-id=\"34feb10\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-35da58d elementor-widget__width-initial elementor-widget elementor-widget-text-editor\" data-id=\"35da58d\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p style=\"text-align: center;\">09:10-09:50<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"has_eae_slider aux-parallax-section elementor-column elementor-col-33 elementor-top-column elementor-element elementor-element-1d18863\" data-id=\"1d18863\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-6e81408 elementor-widget__width-initial elementor-widget elementor-widget-text-editor\" data-id=\"6e81408\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><a href=\"https:\/\/hkubs-stat.github.io\/HKU-2024-Summer-Workshop\/sessions#Iain_Johnstone_abstract\">Expectation Propagation and Maximum Likelihood in Generalized Linear Mixed Models<\/a><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"has_eae_slider aux-parallax-section elementor-column elementor-col-33 elementor-top-column elementor-element elementor-element-00a6aae\" data-id=\"00a6aae\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-9ad289e elementor-widget__width-initial elementor-widget elementor-widget-text-editor\" data-id=\"9ad289e\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>Iain Johnstone<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"has_eae_slider elementor-section elementor-top-section elementor-element elementor-element-2aaade1 elementor-section-stretched elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"2aaade1\" data-element_type=\"section\" data-settings=\"{&quot;stretch_section&quot;:&quot;section-stretched&quot;}\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-no\">\n\t\t\t\t\t<div class=\"has_eae_slider aux-parallax-section elementor-column elementor-col-33 elementor-top-column elementor-element elementor-element-f5f5564\" data-id=\"f5f5564\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-b1dc2ad elementor-widget__width-initial elementor-widget elementor-widget-text-editor\" data-id=\"b1dc2ad\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p style=\"text-align: center;\">09:50-10:00<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"has_eae_slider aux-parallax-section elementor-column elementor-col-33 elementor-top-column elementor-element elementor-element-3cfb0cf\" data-id=\"3cfb0cf\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-bc88726 elementor-widget__width-initial elementor-widget elementor-widget-text-editor\" data-id=\"bc88726\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>Photo<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"has_eae_slider aux-parallax-section elementor-column elementor-col-33 elementor-top-column elementor-element elementor-element-28a4515\" data-id=\"28a4515\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-48a255b elementor-widget__width-initial elementor-widget elementor-widget-text-editor\" data-id=\"48a255b\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"has_eae_slider elementor-section elementor-top-section elementor-element elementor-element-dce867f elementor-section-stretched elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"dce867f\" data-element_type=\"section\" data-settings=\"{&quot;stretch_section&quot;:&quot;section-stretched&quot;,&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-no\">\n\t\t\t\t\t<div class=\"has_eae_slider aux-parallax-section elementor-column elementor-col-33 elementor-top-column elementor-element elementor-element-aa89073\" data-id=\"aa89073\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-0074d0e elementor-widget__width-initial elementor-widget elementor-widget-text-editor\" data-id=\"0074d0e\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p style=\"text-align: center;\">10:00-10:30<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"has_eae_slider aux-parallax-section elementor-column elementor-col-33 elementor-top-column elementor-element elementor-element-560c81f\" data-id=\"560c81f\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-c7adf85 elementor-widget__width-initial elementor-widget elementor-widget-text-editor\" data-id=\"c7adf85\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>Coffee Break<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"has_eae_slider aux-parallax-section elementor-column elementor-col-33 elementor-top-column elementor-element elementor-element-614a41b\" data-id=\"614a41b\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-c203ccc elementor-widget__width-initial elementor-widget elementor-widget-text-editor\" data-id=\"c203ccc\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"has_eae_slider elementor-section elementor-top-section elementor-element elementor-element-18a4439 elementor-section-stretched elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"18a4439\" data-element_type=\"section\" data-settings=\"{&quot;stretch_section&quot;:&quot;section-stretched&quot;}\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-no\">\n\t\t\t\t\t<div class=\"has_eae_slider aux-parallax-section elementor-column elementor-col-50 elementor-top-column elementor-element elementor-element-adeeae1\" data-id=\"adeeae1\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-a942703 elementor-widget__width-initial elementor-widget elementor-widget-text-editor\" data-id=\"a942703\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"has_eae_slider aux-parallax-section elementor-column elementor-col-50 elementor-top-column elementor-element elementor-element-5e62ceb\" data-id=\"5e62ceb\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-39f28b9 elementor-widget__width-initial elementor-widget elementor-widget-text-editor\" data-id=\"39f28b9\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><strong>Session 2, Chair: Dan Yang<\/strong><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"has_eae_slider elementor-section elementor-top-section elementor-element elementor-element-afd7c7e elementor-section-stretched elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"afd7c7e\" data-element_type=\"section\" data-settings=\"{&quot;stretch_section&quot;:&quot;section-stretched&quot;,&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-no\">\n\t\t\t\t\t<div class=\"has_eae_slider aux-parallax-section elementor-column elementor-col-33 elementor-top-column elementor-element elementor-element-0e87b72\" data-id=\"0e87b72\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-fd1754b elementor-widget__width-initial elementor-widget elementor-widget-text-editor\" data-id=\"fd1754b\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p style=\"text-align: center;\">10:30-11:10<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"has_eae_slider aux-parallax-section elementor-column elementor-col-33 elementor-top-column elementor-element elementor-element-b73b068\" data-id=\"b73b068\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-fd283d6 elementor-widget__width-initial elementor-widget elementor-widget-text-editor\" data-id=\"fd283d6\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><a href=\"https:\/\/hkubs-stat.github.io\/HKU-2024-Summer-Workshop\/sessions#Minge_Xie_abstract\">Repro Samples Method and Principled Random Forests<\/a><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"has_eae_slider aux-parallax-section elementor-column elementor-col-33 elementor-top-column elementor-element elementor-element-808fbb9\" data-id=\"808fbb9\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-4916626 elementor-widget__width-initial elementor-widget elementor-widget-text-editor\" data-id=\"4916626\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>Min-ge Xie<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"has_eae_slider elementor-section elementor-top-section elementor-element elementor-element-0834c2e elementor-section-stretched elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"0834c2e\" data-element_type=\"section\" data-settings=\"{&quot;stretch_section&quot;:&quot;section-stretched&quot;}\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-no\">\n\t\t\t\t\t<div class=\"has_eae_slider aux-parallax-section elementor-column elementor-col-33 elementor-top-column elementor-element elementor-element-1cb4c1a\" data-id=\"1cb4c1a\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-d0ea218 elementor-widget__width-initial elementor-widget elementor-widget-text-editor\" data-id=\"d0ea218\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p style=\"text-align: center;\">11:10-11:50<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"has_eae_slider aux-parallax-section elementor-column elementor-col-33 elementor-top-column elementor-element elementor-element-771e9f7\" data-id=\"771e9f7\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-01b4c94 elementor-widget__width-initial elementor-widget elementor-widget-text-editor\" data-id=\"01b4c94\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><a href=\"https:\/\/hkubs-stat.github.io\/HKU-2024-Summer-Workshop\/sessions#Qiman_Shao_abstract\">High Dimensional Gaussian Approximation<\/a><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"has_eae_slider aux-parallax-section elementor-column elementor-col-33 elementor-top-column elementor-element elementor-element-37d4928\" data-id=\"37d4928\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-cee735f elementor-widget__width-initial elementor-widget elementor-widget-text-editor\" data-id=\"cee735f\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>Qiman Shao<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"has_eae_slider elementor-section elementor-top-section elementor-element elementor-element-289a2d3 elementor-section-stretched elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"289a2d3\" data-element_type=\"section\" data-settings=\"{&quot;stretch_section&quot;:&quot;section-stretched&quot;,&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-no\">\n\t\t\t\t\t<div class=\"has_eae_slider aux-parallax-section elementor-column elementor-col-33 elementor-top-column elementor-element elementor-element-51db5b8\" data-id=\"51db5b8\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-1d97d6c elementor-widget__width-initial elementor-widget elementor-widget-text-editor\" data-id=\"1d97d6c\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p style=\"text-align: center;\">11:50-14:30<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"has_eae_slider aux-parallax-section elementor-column elementor-col-33 elementor-top-column elementor-element elementor-element-eb88bb4\" data-id=\"eb88bb4\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-06dba1e elementor-widget__width-initial elementor-widget elementor-widget-text-editor\" data-id=\"06dba1e\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>Lunch Break<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"has_eae_slider aux-parallax-section elementor-column elementor-col-33 elementor-top-column elementor-element elementor-element-88cffec\" data-id=\"88cffec\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-fde802e elementor-widget__width-initial elementor-widget elementor-widget-text-editor\" data-id=\"fde802e\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"has_eae_slider elementor-section elementor-top-section elementor-element elementor-element-1dfb03a elementor-section-stretched elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"1dfb03a\" data-element_type=\"section\" data-settings=\"{&quot;stretch_section&quot;:&quot;section-stretched&quot;,&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-no\">\n\t\t\t\t\t<div class=\"has_eae_slider aux-parallax-section elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-25cb8ff\" data-id=\"25cb8ff\" data-element_type=\"column\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-8085777 elementor-widget elementor-widget-aux_modern_heading\" data-id=\"8085777\" data-element_type=\"widget\" data-widget_type=\"aux_modern_heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<section class=\"aux-widget-modern-heading\">\n            <div class=\"aux-widget-inner\"><h2 class=\"aux-modern-heading-primary\">Afternoon Sessions<\/h2><h3 class=\"aux-modern-heading-secondary\"><span class=\"aux-head-highlight\">Venue: HKU-iCube, Room 4005-07, Two Exchange Square, 8 Connaught Place, Central, Hong Kong.<\/span><\/h3><\/div>\n        <\/section>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"has_eae_slider elementor-section elementor-top-section elementor-element elementor-element-bdc728e elementor-section-stretched elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"bdc728e\" data-element_type=\"section\" data-settings=\"{&quot;stretch_section&quot;:&quot;section-stretched&quot;}\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-no\">\n\t\t\t\t\t<div class=\"has_eae_slider aux-parallax-section elementor-column elementor-col-50 elementor-top-column elementor-element elementor-element-ffa3583\" data-id=\"ffa3583\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-e596c14 elementor-widget__width-initial elementor-widget elementor-widget-text-editor\" data-id=\"e596c14\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"has_eae_slider aux-parallax-section elementor-column elementor-col-50 elementor-top-column elementor-element elementor-element-8a9fdb2\" data-id=\"8a9fdb2\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-dc9dbb6 elementor-widget__width-initial elementor-widget elementor-widget-text-editor\" data-id=\"dc9dbb6\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><strong>Session 3, Chair: Xinghao Qiao<\/strong><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"has_eae_slider elementor-section elementor-top-section elementor-element elementor-element-3467a84 elementor-section-stretched elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"3467a84\" data-element_type=\"section\" data-settings=\"{&quot;stretch_section&quot;:&quot;section-stretched&quot;,&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-no\">\n\t\t\t\t\t<div class=\"has_eae_slider aux-parallax-section elementor-column elementor-col-33 elementor-top-column elementor-element elementor-element-dbe343a\" data-id=\"dbe343a\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-055e39d elementor-widget__width-initial elementor-widget elementor-widget-text-editor\" data-id=\"055e39d\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p style=\"text-align: center;\">14:30-15:10<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"has_eae_slider aux-parallax-section elementor-column elementor-col-33 elementor-top-column elementor-element elementor-element-2c5965e\" data-id=\"2c5965e\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-b22d1f3 elementor-widget__width-initial elementor-widget elementor-widget-text-editor\" data-id=\"b22d1f3\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><a href=\"https:\/\/hkubs-stat.github.io\/HKU-2024-Summer-Workshop\/sessions#Qiwei_Yao_abstract\">Autoregressive Networks with Dependent Edges<\/a><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"has_eae_slider aux-parallax-section elementor-column elementor-col-33 elementor-top-column elementor-element elementor-element-8f3c002\" data-id=\"8f3c002\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-251d8c3 elementor-widget__width-initial elementor-widget elementor-widget-text-editor\" data-id=\"251d8c3\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>Qiwei Yao<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"has_eae_slider elementor-section elementor-top-section elementor-element elementor-element-b199d89 elementor-section-stretched elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"b199d89\" data-element_type=\"section\" data-settings=\"{&quot;stretch_section&quot;:&quot;section-stretched&quot;}\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-no\">\n\t\t\t\t\t<div class=\"has_eae_slider aux-parallax-section elementor-column elementor-col-33 elementor-top-column elementor-element elementor-element-6cfd7cd\" data-id=\"6cfd7cd\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-12b4eb9 elementor-widget__width-initial elementor-widget elementor-widget-text-editor\" data-id=\"12b4eb9\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p style=\"text-align: center;\">15:10-15:50<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"has_eae_slider aux-parallax-section elementor-column elementor-col-33 elementor-top-column elementor-element elementor-element-036aaef\" data-id=\"036aaef\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-8806dd3 elementor-widget__width-initial elementor-widget elementor-widget-text-editor\" data-id=\"8806dd3\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><a href=\"https:\/\/hkubs-stat.github.io\/HKU-2024-Summer-Workshop\/sessions#Yongtao_Guan_abstract\">Bias-Correction and Test for Mark-Point Dependence with Replicated Marked Point Processes<\/a><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"has_eae_slider aux-parallax-section elementor-column elementor-col-33 elementor-top-column elementor-element elementor-element-da986ca\" data-id=\"da986ca\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-f9d1a55 elementor-widget__width-initial elementor-widget elementor-widget-text-editor\" data-id=\"f9d1a55\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>Yongtao Guan<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"has_eae_slider elementor-section elementor-top-section elementor-element elementor-element-1778031 elementor-section-stretched elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"1778031\" data-element_type=\"section\" data-settings=\"{&quot;stretch_section&quot;:&quot;section-stretched&quot;,&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-no\">\n\t\t\t\t\t<div class=\"has_eae_slider aux-parallax-section elementor-column elementor-col-33 elementor-top-column elementor-element elementor-element-d81208e\" data-id=\"d81208e\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-c4c18a1 elementor-widget__width-initial elementor-widget elementor-widget-text-editor\" data-id=\"c4c18a1\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p style=\"text-align: center;\">15:50-16:20<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"has_eae_slider aux-parallax-section elementor-column elementor-col-33 elementor-top-column elementor-element elementor-element-625feaf\" data-id=\"625feaf\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-7522a1a elementor-widget__width-initial elementor-widget elementor-widget-text-editor\" data-id=\"7522a1a\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>Coffee Break<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"has_eae_slider aux-parallax-section elementor-column elementor-col-33 elementor-top-column elementor-element elementor-element-64741ee\" data-id=\"64741ee\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-619c04e elementor-widget__width-initial elementor-widget elementor-widget-text-editor\" data-id=\"619c04e\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"has_eae_slider elementor-section elementor-top-section elementor-element elementor-element-fbff982 elementor-section-stretched elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"fbff982\" data-element_type=\"section\" data-settings=\"{&quot;stretch_section&quot;:&quot;section-stretched&quot;}\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-no\">\n\t\t\t\t\t<div class=\"has_eae_slider aux-parallax-section elementor-column elementor-col-50 elementor-top-column elementor-element elementor-element-7ce5691\" data-id=\"7ce5691\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-0cee691 elementor-widget__width-initial elementor-widget elementor-widget-text-editor\" data-id=\"0cee691\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"has_eae_slider aux-parallax-section elementor-column elementor-col-50 elementor-top-column elementor-element elementor-element-ef4e193\" data-id=\"ef4e193\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-86c148c elementor-widget__width-initial elementor-widget elementor-widget-text-editor\" data-id=\"86c148c\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><strong>Session 4, Chair: Zhanrui Cai<\/strong><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"has_eae_slider elementor-section elementor-top-section elementor-element elementor-element-a74ab3b elementor-section-stretched elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"a74ab3b\" data-element_type=\"section\" data-settings=\"{&quot;stretch_section&quot;:&quot;section-stretched&quot;,&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-no\">\n\t\t\t\t\t<div class=\"has_eae_slider aux-parallax-section elementor-column elementor-col-33 elementor-top-column elementor-element elementor-element-09cf0f6\" data-id=\"09cf0f6\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-4a96a1c elementor-widget__width-initial elementor-widget elementor-widget-text-editor\" data-id=\"4a96a1c\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p style=\"text-align: center;\">16:20-17:00<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"has_eae_slider aux-parallax-section elementor-column elementor-col-33 elementor-top-column elementor-element elementor-element-4de6a21\" data-id=\"4de6a21\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-76fb2ce elementor-widget__width-initial elementor-widget elementor-widget-text-editor\" data-id=\"76fb2ce\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><a href=\"https:\/\/hkubs-stat.github.io\/HKU-2024-Summer-Workshop\/sessions#Runze_Li_abstract\">Model-Free Statistical Inference on High-Dimensional Data<\/a><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"has_eae_slider aux-parallax-section elementor-column elementor-col-33 elementor-top-column elementor-element elementor-element-2fe06c2\" data-id=\"2fe06c2\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-c54fa13 elementor-widget__width-initial elementor-widget elementor-widget-text-editor\" data-id=\"c54fa13\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>Runze Li<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"has_eae_slider elementor-section elementor-top-section elementor-element elementor-element-64a9d3d elementor-section-stretched elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"64a9d3d\" data-element_type=\"section\" data-settings=\"{&quot;stretch_section&quot;:&quot;section-stretched&quot;}\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-no\">\n\t\t\t\t\t<div class=\"has_eae_slider aux-parallax-section elementor-column elementor-col-33 elementor-top-column elementor-element elementor-element-d26bb84\" data-id=\"d26bb84\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-e84912b elementor-widget__width-initial elementor-widget elementor-widget-text-editor\" data-id=\"e84912b\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p style=\"text-align: center;\">17:00-17:40<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"has_eae_slider aux-parallax-section elementor-column elementor-col-33 elementor-top-column elementor-element elementor-element-af34592\" data-id=\"af34592\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-df822f3 elementor-widget__width-initial elementor-widget elementor-widget-text-editor\" data-id=\"df822f3\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><a href=\"https:\/\/hkubs-stat.github.io\/HKU-2024-Summer-Workshop\/sessions#Yingying_Li_abstract\">Learning the Stochastic Discount Factor<\/a><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"has_eae_slider aux-parallax-section elementor-column elementor-col-33 elementor-top-column elementor-element elementor-element-bb9f7f9\" data-id=\"bb9f7f9\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-48b61a5 elementor-widget__width-initial elementor-widget elementor-widget-text-editor\" data-id=\"48b61a5\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>Yingying Li<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"has_eae_slider elementor-section elementor-top-section elementor-element elementor-element-c5fbc14 elementor-section-stretched elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"c5fbc14\" data-element_type=\"section\" data-settings=\"{&quot;stretch_section&quot;:&quot;section-stretched&quot;,&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-no\">\n\t\t\t\t\t<div class=\"has_eae_slider aux-parallax-section elementor-column elementor-col-33 elementor-top-column elementor-element elementor-element-fe4059e\" data-id=\"fe4059e\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-2df6642 elementor-widget__width-initial elementor-widget elementor-widget-text-editor\" data-id=\"2df6642\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p style=\"text-align: center;\">17:40-17:50<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"has_eae_slider aux-parallax-section elementor-column elementor-col-33 elementor-top-column elementor-element elementor-element-9dfa089\" data-id=\"9dfa089\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-ad726c3 elementor-widget__width-initial elementor-widget elementor-widget-text-editor\" data-id=\"ad726c3\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>Closing: Dan Yang<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"has_eae_slider aux-parallax-section elementor-column elementor-col-33 elementor-top-column elementor-element elementor-element-a4ee472\" data-id=\"a4ee472\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-8723f91 elementor-widget__width-initial elementor-widget elementor-widget-text-editor\" data-id=\"8723f91\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"has_eae_slider elementor-section elementor-top-section elementor-element elementor-element-aa64270 elementor-section-stretched elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"aa64270\" data-element_type=\"section\" data-settings=\"{&quot;stretch_section&quot;:&quot;section-stretched&quot;}\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-no\">\n\t\t\t\t\t<div class=\"has_eae_slider aux-parallax-section elementor-column elementor-col-50 elementor-top-column elementor-element elementor-element-9abd13a\" data-id=\"9abd13a\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-7794168 elementor-widget__width-initial elementor-widget elementor-widget-text-editor\" data-id=\"7794168\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p style=\"text-align: center;\">17:50-20:30<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"has_eae_slider aux-parallax-section elementor-column elementor-col-50 elementor-top-column elementor-element elementor-element-3b4ce7a\" data-id=\"3b4ce7a\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-bbb8f5e elementor-widget__width-initial elementor-widget-mobile__width-initial elementor-widget elementor-widget-text-editor\" data-id=\"bbb8f5e\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>Banquet (invitation only)<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"has_eae_slider elementor-section elementor-top-section elementor-element elementor-element-ede4ded elementor-section-stretched elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"ede4ded\" data-element_type=\"section\" data-settings=\"{&quot;stretch_section&quot;:&quot;section-stretched&quot;,&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"has_eae_slider aux-parallax-section elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-54a4770\" data-id=\"54a4770\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-c761c0f elementor-widget elementor-widget-aux_modern_heading\" data-id=\"c761c0f\" data-element_type=\"widget\" data-widget_type=\"aux_modern_heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<section class=\"aux-widget-modern-heading\">\n            <div class=\"aux-widget-inner\"><h2 class=\"aux-modern-heading-primary\">Abstracts of the talks<\/h2><\/div>\n        <\/section>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"has_eae_slider elementor-section elementor-top-section elementor-element elementor-element-f317d57 elementor-section-stretched elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"f317d57\" data-element_type=\"section\" data-settings=\"{&quot;stretch_section&quot;:&quot;section-stretched&quot;}\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"has_eae_slider aux-parallax-section elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-48dd366\" data-id=\"48dd366\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-2b47652 elementor-widget elementor-widget-text-editor\" data-id=\"2b47652\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><strong>Expectation Propagation and Maximum Likelihood in Generalized Linear Mixed Models<\/strong><\/p><p>Iain Johnstone (Stanford University)<\/p><p>We consider a class of generalized linear mixed models in which both the number of groups and the number of observations within each group are large, and in which usual likelihood analysis encounters both computational and technical challenges. Matt Wand and colleagues have adapted the machine learning technique of expectation propagation (EP) to yield state-of-the-art estimation of parameters in such models. Here we ask: are the EP estimators asymptotically efficient? A main challenge is to define an appropriate objective function that captures the EP iteration and approximates maximum likelihood well enough to inherit its efficiency. A second issue is to show that maximum likelihood actually is efficient, due to integrals over random effects in the likelihood. For this we propose a novel method based on classical complex analysis. This is joint work with a group including the late Peter Hall, Matt Wand, Song Mei and Apratim Dey.<\/p><p><br \/><strong>Repro Samples Method and Principled Random Forests<br \/><\/strong><br \/>Min-ge Xie (Rutgers University)<br \/><br \/>Repro Samples method introduces a fundamentally new inferential framework that can be used to effectively address frequently encountered, yet highly non-trivial and complex inference problems involving discrete or non-numerical unknown parameters and\/or non-numerical data. In this talk, we present a set of key developments in the repro samples method and use them to develop a novel machine learning ensemble tree model, termed principled random forests. Specifically, repro samples are artificial samples that are reproduced by mimicking the genesis of observed data. Using the repro samples and inversion techniques stemmed from fiducial inference, we can establish a confidence set for the underlying (\u2018true\u2019) tree model that generated, or approximately generated, the observed data.<br \/>We then obtain a tree ensemble model using the confidence set, from which we derive our inference. Our development is principled and interpretable since, firstly, it is fully theoretically supported and provides frequentist performance guarantees on both inference and predictions; and secondly, the approach only assembles a small set of trees in the confidence set and thereby the model used is interpretable. The development is further extended to handle a causal inference setting of heterogeneous treatment effects. Numerical results have demonstrated superior performance of our proposed approach than several existing poste selection, random forest, bagging, and causal trees ensemble methods.<br \/>The repro samples method provides a new toolset for developing interpretable AI and for helping address the blackbox issues in complex machine learning models. The development of the principle random forest is our first attempt on this direction.<br \/><br \/><\/p><p><strong>High Dimensional Gaussian Approximation<br \/><\/strong><br \/>Qiman Shao (Southern University of Science and Technology)<br \/><br \/>BerryEsseen type bounds for Gaussian approximation of standardized sums have been extensively studied under finite moment conditions for lower dimensional data and under sub-exponential moment conditions for high dimensional data. However, since the standardized coefficients such as the population standard deviations are typically unknown, it is essential for statistical inference to study the high dimensional Gaussian approximation of self-normalized sums. In this talk , we shall give a brief review on self-normalized limit theory and establish a Cramer type moderate deviation theorem for self-normalized Gaussian approximation under finite moment conditions.<\/p><p><br \/><strong>Autoregressive Networks with Dependent Edges<br \/><\/strong><br \/>Qiwei Yao (The London School of Economics and Political Science)<br \/><br \/>We propose an autoregressive framework for modelling dynamic networks with dependent edges. It encompasses the models which accommodate, for example, transitivity, density-dependent and other stylized features often observed in real network data. By assuming the edges of network at each time are independent conditionally on their lagged values, the models, which exhibit a close connection with temporal ERGMs, facilitate both simulation and the maximum likelihood estimation in the straightforward manner. Due to the possible large number of parameters in the models, the initial MLEs may suffer from slow convergence rates. An improved estimator for each component parameter is proposed based on an iteration based on the projection which mitigates the impact of the other parameters. Based on a martingale difference structure, the asymptotic distribution of the improved estimator is derived without the stationarityassumption. The limiting distribution is not normal in general, and it reduces to normal when the underlying process satisfies some mixing conditions. Illustration with a transitivity model was carried out in both simulation and two real network data sets.<br \/><br \/><br \/><strong>Bias-Correction and Test for Mark-Point Dependence with Replicated Marked Point Processes<br \/><\/strong><br \/>Yongtao Guan (The Chinese University of Hong Kong, Shenzhen)<br \/><br \/>Mark-point dependence plays a critical role in research problems that can be fitted into the general framework of marked point processes. In this work, we focus on adjusting for mark-point dependence when estimating the mean and covariance functions of the mark process, given independent replicates of the marked point process. We assume that the mark process is a Gaussian process and the point process is a log-Gaussian Cox process, where the mark-point dependence is generated through the dependence between two latent Gaussian processes. Under this framework, naive local linear estimators ignoring the mark-point dependence can be severely biased. We show that this bias can be corrected using a local linear estimator of the cross-covariance function and establish uniform convergence rates of the bias-corrected estimators. Furthermore, we propose a test statistic based on local linear estimators for mark-point independence, which is shown to converge to an asymptotic normal distribution in a parametric root n convergence rate. Model diagnostics tools are developed for key model assumptions and a robust functional permutation test is proposed for a more general class of mark-point processes. The effectiveness of the proposed methods is demonstrated using extensive simulations and applications to some real data examples.<br \/><br \/><br \/><strong>Model-Free Statistical Inference on High-Dimensional Data<br \/><\/strong><br \/>Runze Li (Pennsylvania State University)<br \/><br \/>This paper aims to develop an effective model-free inference procedure for high-dimensional data. We first reformulate the hypothesis testing problem via sufficient dimension reduction framework. With the aid of new reformulation, we propose a new test statistic and show that its asymptotic distribution is\u00a0\u03c7<sup>2<\/sup>\u00a0distribution whose degree of freedom does not depend on the unknown population distribution. We further conduct power analysis under local alternative hypotheses. In addition, we study how to control the false discovery rate of the proposed\u00a0\u03c7<sup>2<\/sup>\u00a0tests, which are correlated, to identify important predictors under a model-free framework. To this end, we propose a multiple testing procedure and establish its theoretical guarantees. Monte Carlo simulation studies are conducted to assess the performance of the proposed tests and an empirical analysis of a real-world data set is used to illustrate the proposed methodology.<br \/><br \/><br \/><strong>Learning the Stochastic Discount Factor<br \/><\/strong><br \/>Yingying Li (Hong Kong University of Science and Technology)<br \/><br \/>We develop a statistical framework to learn the high-dimensional stochastic discount factor (SDF) from a large set of characteristic-based portfolios. Specifically, we build on the maximum-Sharpe ratio estimated and sparse regression method proposed in Ao, Li and Zheng (RFS,2019) to construct the SDF portfolio, and develop a statistical inference theory to test the SDF loadings. Applying our approach to 194 characteristic-based portfolios, we find that the SDF constructed by about 20 of them performs well in achieving a high Sharpe ratio and explaining the cross-section of expected returns of various portfolios. Joint work with Zhanhui Chen, Yi Ding and Xinghua Zheng.<br \/><br \/><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"has_eae_slider elementor-section elementor-top-section elementor-element elementor-element-1d60ce4 elementor-section-full_width elementor-section-stretched elementor-section-height-default elementor-section-height-default\" data-id=\"1d60ce4\" data-element_type=\"section\" data-settings=\"{&quot;stretch_section&quot;:&quot;section-stretched&quot;}\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-no\">\n\t\t\t\t\t<div class=\"has_eae_slider aux-parallax-section elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-9764e92\" data-id=\"9764e92\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-e0fde0d elementor-widget elementor-widget-menu-anchor\" data-id=\"e0fde0d\" data-element_type=\"widget\" data-widget_type=\"menu-anchor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div id=\"organizing_committee\" class=\"elementor-menu-anchor\"><\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"has_eae_slider elementor-section elementor-top-section elementor-element elementor-element-b18cab5 elementor-section-full_width elementor-section-stretched elementor-section-height-default elementor-section-height-default\" data-id=\"b18cab5\" data-element_type=\"section\" data-settings=\"{&quot;stretch_section&quot;:&quot;section-stretched&quot;}\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-no\">\n\t\t\t\t\t<div class=\"has_eae_slider aux-parallax-section elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-fda5410\" data-id=\"fda5410\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-a22cb9d elementor-widget elementor-widget-menu-anchor\" data-id=\"a22cb9d\" data-element_type=\"widget\" data-widget_type=\"menu-anchor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div id=\"for_enquiry\" class=\"elementor-menu-anchor\"><\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"has_eae_slider elementor-section elementor-top-section elementor-element elementor-element-8d9e8e1 elementor-section-full_width elementor-section-stretched elementor-section-height-default elementor-section-height-default\" data-id=\"8d9e8e1\" data-element_type=\"section\" data-settings=\"{&quot;stretch_section&quot;:&quot;section-stretched&quot;}\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-no\">\n\t\t\t\t\t<div class=\"has_eae_slider aux-parallax-section elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-f7796f1\" data-id=\"f7796f1\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-046d75b elementor-widget elementor-widget-html\" data-id=\"046d75b\" data-element_type=\"widget\" data-widget_type=\"html.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style type=\"text\/css\">\r\n.elementor-menu-anchor {\r\n    margin-top: -150px;\r\n    padding-top: 150px;\r\n    width: 0px;\r\n}\r\n@media (max-width: 1024px){\r\n.elementor-menu-anchor {\r\n    margin-top: -90px;\r\n    padding-top: 90px;\r\n    width: 0px;\r\n}\r\n}\r\n@media (max-width: 767px){\r\n.elementor-menu-anchor {\r\n    margin-top: -60px;\r\n    padding-top: 60px;\r\n    width: 0px;\r\n}\r\n}\r\n<\/style>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>Workshop Program A PDF version of this page can be found\u00a0here. Morning Sessions Venue: CPD-3.28, Central Podium Levels \u2013 Three (CPD-3,\u00a0The Jockey Club Tower), Centennial Campus, HKU. 08:30-09:00 Registration 09:00-09:10 Opening: Haipeng Shen Session 1, Chair: Weichen Wang 09:10-09:50 Expectation Propagation and Maximum Likelihood in Generalized Linear Mixed Models Iain Johnstone 09:50-10:00 Photo 10:00-10:30 Coffee [&hellip;]<\/p>\n","protected":false},"author":3,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"folder":[17],"class_list":["post-717","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/www.hkubs.hku.hk\/eventsite\/iim-summer-workshop-2024\/wp-json\/wp\/v2\/pages\/717"}],"collection":[{"href":"https:\/\/www.hkubs.hku.hk\/eventsite\/iim-summer-workshop-2024\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.hkubs.hku.hk\/eventsite\/iim-summer-workshop-2024\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.hkubs.hku.hk\/eventsite\/iim-summer-workshop-2024\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/www.hkubs.hku.hk\/eventsite\/iim-summer-workshop-2024\/wp-json\/wp\/v2\/comments?post=717"}],"version-history":[{"count":85,"href":"https:\/\/www.hkubs.hku.hk\/eventsite\/iim-summer-workshop-2024\/wp-json\/wp\/v2\/pages\/717\/revisions"}],"predecessor-version":[{"id":954,"href":"https:\/\/www.hkubs.hku.hk\/eventsite\/iim-summer-workshop-2024\/wp-json\/wp\/v2\/pages\/717\/revisions\/954"}],"wp:attachment":[{"href":"https:\/\/www.hkubs.hku.hk\/eventsite\/iim-summer-workshop-2024\/wp-json\/wp\/v2\/media?parent=717"}],"wp:term":[{"taxonomy":"folder","embeddable":true,"href":"https:\/\/www.hkubs.hku.hk\/eventsite\/iim-summer-workshop-2024\/wp-json\/wp\/v2\/folder?post=717"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}