Events

Tensors are higher-order generalizations of matrices. Technological advances over the past few decades have made large-scale tensor data ubiquitous across fields such as econometrics, complex networks, and time-series analysis. This talk will first review recent methodological and algorithmic developments in tensor data analysis, along with representative applications. The second part will focus on two specific topics: tensor clustering and tensor completion,  highlighting minimax optimality, computational hardness, statistical inference, and the interplay among these themes.