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Poster
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Tue 14:00
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Quantum Speedups of Optimizing Approximately Convex Functions with Applications to Logarithmic Regret Stochastic Convex Bandits
Tongyang Li · Ruizhe Zhang
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Poster
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Tue 14:00
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Reinforcement Learning with Logarithmic Regret and Policy Switches
Grigoris Velegkas · Zhuoran Yang · Amin Karbasi
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Poster
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Thu 14:00
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Efficient and Near-Optimal Smoothed Online Learning for Generalized Linear Functions
Adam Block · Max Simchowitz
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Poster
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On the role of overparameterization in off-policy Temporal Difference learning with linear function approximation
Valentin Thomas
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Poster
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Thu 14:00
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First-Order Algorithms for Min-Max Optimization in Geodesic Metric Spaces
Michael Jordan · Tianyi Lin · Emmanouil-Vasileios Vlatakis-Gkaragkounis
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Poster
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Tue 14:00
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Frank-Wolfe-based Algorithms for Approximating Tyler's M-estimator
Lior Danon · Dan Garber
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Workshop
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Fri 12:15
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Low Rank Approximation for Faster Convex Optimization
Madeleine Udell
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Poster
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Tue 9:00
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Safety Guarantees for Neural Network Dynamic Systems via Stochastic Barrier Functions
Rayan Mazouz · Karan Muvvala · Akash Ratheesh Babu · Luca Laurenti · Morteza Lahijanian
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Poster
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Wed 14:00
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Decomposable Non-Smooth Convex Optimization with Nearly-Linear Gradient Oracle Complexity
Sally Dong · Haotian Jiang · Yin Tat Lee · Swati Padmanabhan · Guanghao Ye
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Poster
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Tue 14:00
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A Statistical Online Inference Approach in Averaged Stochastic Approximation
Chuhan Xie · Zhihua Zhang
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Poster
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Tue 9:00
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Instance-Dependent Near-Optimal Policy Identification in Linear MDPs via Online Experiment Design
Andrew Wagenmaker · Kevin Jamieson
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Workshop
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A General Framework for Sample-Efficient Function Approximation in Reinforcement Learning
Zixiang Chen · Chris Junchi Li · Angela Yuan · Quanquan Gu · Michael Jordan
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