
No Regrets for Learning the Prior in Bandits
We propose AdaTS, a Thompson sampling algorithm that adapts sequentially...
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Episodic Bandits with Stochastic Experts
We study a version of the contextual bandit problem where an agent is gi...
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Combinatorial Blocking Bandits with Stochastic Delays
Recent work has considered natural variations of the multiarmed bandit ...
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Beyond log^2(T) Regret for Decentralized Bandits in Matching Markets
We design decentralized algorithms for regret minimization in the twosi...
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Robust Estimation of Tree Structured Markov Random Fields
We study the problem of learning treestructured Markov random fields (M...
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On Generalization of Adaptive Methods for Overparameterized Linear Regression
Overparameterization and adaptive methods have played a crucial role in...
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Stochastic Linear Bandits with Protected Subspace
We study a variant of the stochastic linear bandit problem wherein we op...
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Dominate or Delete: Decentralized Competing Bandits with Uniform Valuation
We study regret minimization problems in a twosided matching market whe...
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Contextual Blocking Bandits
We study a novel variant of the multiarmed bandit problem, where at eac...
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Warm Starting Bandits with Side Information from Confounded Data
We study a variant of the multiarmed bandit problem where side informat...
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Blocking Bandits
We consider a novel stochastic multiarmed bandit setting, where playing...
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Disentangling Mixtures of Epidemics on Graphs
We consider the problem of learning the weighted edges of a mixture of t...
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Towards a Functional Fee Market for Cryptocurrencies
Blockchainbased cryptocurrencies prioritize transactions based on their...
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Asynchronous Verifiable SecretSharing Protocols on a Good Day
Asynchronous verifiable secret sharing (AVSS) is a cornerstone primitive...
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Decentralization in Bitcoin and Ethereum Networks
Blockchainbased cryptocurrencies have demonstrated how to securely impl...
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Soumya Basu
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