Results

Poster	Wed 0:30	Rate-Optimal Subspace Estimation on Random Graphs Zhixin Zhou · Fan Zhou · Ping Li · Cun-Hui Zhang
Poster	Thu 0:30	Near-Optimal Multi-Perturbation Experimental Design for Causal Structure Learning Scott Sussex · Caroline Uhler · Andreas Krause
Poster	Tue 8:30	$\texttt{LeadCache}$: Regret-Optimal Caching in Networks Debjit Paria · Abhishek Sinha
Poster	Thu 16:30	A Biased Graph Neural Network Sampler with Near-Optimal Regret Qingru Zhang · David Wipf · Quan Gan · Le Song
Poster	Fri 8:30	Optimization-Based Algebraic Multigrid Coarsening Using Reinforcement Learning Ali Taghibakhshi · Scott MacLachlan · Luke Olson · Matthew West
Poster	Thu 8:30	A Near-Optimal Algorithm for Stochastic Bilevel Optimization via Double-Momentum Prashant Khanduri · Siliang Zeng · Mingyi Hong · Hoi-To Wai · Zhaoran Wang · Zhuoran Yang
Poster	Tue 8:30	A Domain-Shrinking based Bayesian Optimization Algorithm with Order-Optimal Regret Performance Sudeep Salgia · Sattar Vakili · Qing Zhao
Oral	Tue 0:20	Near-Optimal No-Regret Learning in General Games Constantinos Daskalakis · Maxwell Fishelson · Noah Golowich
Poster	Thu 16:30	STEM: A Stochastic Two-Sided Momentum Algorithm Achieving Near-Optimal Sample and Communication Complexities for Federated Learning Prashant Khanduri · PRANAY SHARMA · Haibo Yang · Mingyi Hong · Jia Liu · Ketan Rajawat · Pramod Varshney
Poster	Tue 16:30	Near-optimal Offline and Streaming Algorithms for Learning Non-Linear Dynamical Systems Suhas Kowshik · Dheeraj Nagaraj · Prateek Jain · Praneeth Netrapalli
Spotlight		Learning MDPs from Features: Predict-Then-Optimize for Sequential Decision Making by Reinforcement Learning Kai Wang · Sanket Shah · Haipeng Chen · Andrew Perrault · Finale Doshi-Velez · Milind Tambe
Workshop	Mon 9:30	Towards instance-optimized data systems Tim Kraska