Anirban Santara
Anirban Santara is a software engineer at Google Research India. Prior to this, he was a Google PhD Fellow at Indian Institute of Technology Kharagpur where he studied reinforcement learning algorithms for safe and efficient planning in autonomous driving. His current research interests include reinforcement learning for web-scale applications and representation learning for semantic robot navigation.
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Motivated by problems of ranking with partial information, we introduce a variant of the cascading bandit model that considers flexible length sequences with varying rewards and losses. We formulate two generative models for this problem within the generalized linear setting, and design and analyze upper confidence algorithms for it. Our analysis delivers tight regret bounds which, when specialized to standard cascading bandits, results in sharper guarantees than previously available in the literature. We evaluate our algorithms against a representative sample of cascading bandit baselines on a number of real-world datasets and show significantly improved empirical performance.
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A Contextual Bandit Approach for Learning to Plan in Environments with Probabilistic Goal Configurations
Sohan Rudra
Saksham Goel
Gaurav Aggarwal
NeurIPS 5th Robot Learning Workshop: Trustworthy Robotics (2022) (to appear)
