Seminars

Online learning is formulated as a sequential decision problem with partial/censored feedback: an agent acts in an unknown, oblivious environment,…

We present various studies that investigate the head injury and prevention of secondary school athletes, from Hawaii Concussion Awareness and…

In this talk, I will present a unified theoretical framework for clustering methods based on hill-climbing strategies, originally introduced by…

Stochastic simulations are increasingly used to describe complex systems with uncertainties. To better characterize the uncertainty of such a simulation,…

Influential entities can occur in social media, financial markets, energy transmission, you name it. In the presence of short time…

In causal inference, true causal order and the graph of causal interaction can be uniquely determined if you have sufficient…

Quantifying differences between probability distributions is central to statistics and machine learning, primarily for comparing statistical uncertainty. However, epistemic uncertainty—stemming…

General first-order methods (GFOMs), including various gradient descent variants and approximate message passing algorithms, constitute a broad class of iterative…

In today’s data-driven landscape, harnessing vast and varied datasets provides unparalleled opportunities for knowledge extraction and informed decision-making. Yet, within…

Controlling the False Discovery Rate (FDR) with finite sample guarantee in a variable selection procedure is important for trustworthy and…