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Thu Jul 21 12:30 PM -- 12:35 PM (PDT) @ Ballroom 3 & 4
Nearly Optimal Catoni’s M-estimator for Infinite Variance
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Paper PDF]
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Thu Jul 21 12:35 PM -- 12:40 PM (PDT) @ Ballroom 3 & 4
Strategies for Safe Multi-Armed Bandits with Logarithmic Regret and Risk
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Thu Jul 21 12:40 PM -- 12:45 PM (PDT) @ Ballroom 3 & 4
Local Linear Convergence of Douglas-Rachford for Linear Programming: a Probabilistic Analysis
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Paper PDF]
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Thu Jul 21 12:45 PM -- 12:50 PM (PDT) @ Ballroom 3 & 4
Contextual Information-Directed Sampling
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Thu Jul 21 12:50 PM -- 12:55 PM (PDT) @ Ballroom 3 & 4
Breaking the $\sqrt{T}$ Barrier: Instance-Independent Logarithmic Regret in Stochastic Contextual Linear Bandits
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Thu Jul 21 12:55 PM -- 01:00 PM (PDT) @ Ballroom 3 & 4
Universal and data-adaptive algorithms for model selection in linear contextual bandits
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Thu Jul 21 01:00 PM -- 01:05 PM (PDT) @ Ballroom 3 & 4
Regret Minimization with Performative Feedback
Oral
Thu Jul 21 01:05 PM -- 01:25 PM (PDT) @ Ballroom 3 & 4
A Simple yet Universal Strategy for Online Convex Optimization
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Thu Jul 21 01:25 PM -- 01:30 PM (PDT) @ Ballroom 3 & 4
Deep Hierarchy in Bandits
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Thu Jul 21 01:30 PM -- 01:35 PM (PDT) @ Ballroom 3 & 4
Distributionally-Aware Kernelized Bandit Problems for Risk Aversion
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Thu Jul 21 01:35 PM -- 01:40 PM (PDT) @ Ballroom 3 & 4
Asymptotically-Optimal Gaussian Bandits with Side Observations
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Thu Jul 21 01:40 PM -- 01:45 PM (PDT) @ Ballroom 3 & 4
Learning from a Learning User for Optimal Recommendations
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Thu Jul 21 01:45 PM -- 01:50 PM (PDT) @ Ballroom 3 & 4
Thresholded Lasso Bandit
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Thu Jul 21 01:50 PM -- 01:55 PM (PDT) @ Ballroom 3 & 4
Versatile Dueling Bandits: Best-of-both World Analyses for Learning from Relative Preferences
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Thu Jul 21 01:55 PM -- 02:00 PM (PDT) @ Ballroom 3 & 4
Decentralized Online Convex Optimization in Networked Systems