Statistical Learning
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Adaptive Passive-Aggressive Framework for Online Regression with Side Information
Neural Information Processing Systems
To address these challenges, we introduce a novel adaptive framework that allows finer adjustments to the weight vector in P A using side information.
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A Unified Confidence Sequence for Generalized Linear Models, with Applications to Bandits
Neural Information Processing Systems
OFUGLB outperforms or is at par with prior algorithms for logistic bandits.
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Distributional Successor Features Enable Zero-Shot Policy Optimization
Neural Information Processing Systems
Intelligent agents must be generalists, capable of quickly adapting to various tasks.
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