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01/06/2022
Jointly Efficient and Optimal Algorithms for Logistic Bandits
Logistic Bandits have recently undergone careful scrutiny by virtue of t...
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03/09/2021
Regret Bounds for Generalized Linear Bandits under Parameter Drift
Generalized Linear Bandits (GLBs) are powerful extensions to the Linear ...
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11/13/2020
Improving Offline Contextual Bandits with Distributional Robustness
This paper extends the Distributionally Robust Optimization (DRO) approa...
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11/02/2020
Self-Concordant Analysis of Generalized Linear Bandits with Forgetting
Contextual sequential decision problems with categorical or numerical ob...
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10/23/2020
Instance-Wise Minimax-Optimal Algorithms for Logistic Bandits
Logistic Bandits have recently attracted substantial attention, by provi...
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02/18/2020
Improved Optimistic Algorithms for Logistic Bandits
The generalized linear bandit framework has attracted a lot of attention...
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06/14/2019
Distributionally Robust Counterfactual Risk Minimization
This manuscript introduces the idea of using Distributionally Robust Opt...
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01/31/2019
Improving Evolutionary Strategies with Generative Neural Networks
Evolutionary Strategies (ES) are a popular family of black-box zeroth-or...
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05/22/2018
Neural Generative Models for Global Optimization with Gradients
The aim of global optimization is to find the global optimum of arbitrar...
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01/22/2018