Optimization
FDS Colloquium: Xinyi Chen (Princeton University)
Speaker bio: Xinyi Chen is a PhD candidate in the Department of Computer Science at Princeton University, where she is advised by Prof. Elad […]
FDS Colloquium: Brice Huang (MIT), “Algorithmic thresholds in random optimization problems”
Abstract: Optimizing high-dimensional functions generated from random data is a central problem in modern statistics and machine learning. As these objectives are highly non-convex, […]
FDS Seminar: Kumar Kshitij Patel (TTIC)
“Re-inventing Machine Learning for Multiple Distributions: Optimization, Privacy, and Incentives” Abstract: Federated Learning (FL) has emerged as a transformative framework for multi-distribution learning, driving breakthroughs in […]
S&DS Seminar: Jelena Bradic (UCSD), “Dynamic causal inference under model misspecification”
Abstract: Estimating dynamic treatment effects is essential across various disciplines, offering nuanced insights into the time-dependent causal impact of interventions. However, this estimation presents […]
FDS Colloquium: Bento Natura (Columbia), “Faster Exact Linear Programming”
Optional Zoom link: https://yale.zoom.us/j/99342713421 Abstract: We present a novel algorithm to solve various subclasses of linear programs, with a particular focus on strongly polynomial […]
Optimal Guarantees for Algorithmic Reproducibility and Gradient Complexity in Convex Optimization
Liang Zhang, Junchi Yang, Amin Karbasi, Niao He
Liang Zhang, Junchi Yang, Amin Karbasi, Niao He
Yale Theory Student Seminar: Alkis Kalavasis, “Some Open Problems in TCS”
Abstract: “Overview of the things I am interested in (Machine Learning & Optimization)” Question 1 (TCS): Query Complexity of MaxCut and beyond. Question 2 […]
Yale Theory Student Seminar: Felix Zhou, “Applications of Uniform Sampling for Densest Subgraph”
Abstract: We will survey two papers that apply a simple uniform subsampling routine to the densest subgraph problem in the streaming setting. Yale Theory […]
