4 citations · 11 across the 6 of their papers we have counts for
6 papers
Asymptotically-Optimal Gaussian Bandits with Side Observations
Alexia Atsidakou, Orestis Papadigenopoulos, Constantine Caramanis +2
We study the problem of Gaussian bandits with general side information, as first introduced by Wu, Szepesvari, and Gyorgy. In this setting, the play of an arm reveals information a…
Finite-Time Logarithmic Bayes Regret Upper Bounds
Alexia Atsidakou, Branislav Kveton, Sumeet Katariya +2
We derive the first finite-time logarithmic Bayes regret upper bounds for Bayesian bandits. In a multi-armed bandit, we obtain and upper bounds for…
Bayesian Fixed-Budget Best-Arm Identification
Alexia Atsidakou, Sumeet Katariya, Sujay Sanghavi +1
Fixed-budget best-arm identification (BAI) is a bandit problem where the agent maximizes the probability of identifying the optimal arm within a fixed budget of observations. In th…
Contextual Pandora's Box
Alexia Atsidakou, Constantine Caramanis, Evangelia Gergatsouli +2
Pandora's Box is a fundamental stochastic optimization problem, where the decision-maker must find a good alternative while minimizing the search cost of exploring the value of eac…
Towards Statistical and Computational Complexities of Polyak Step Size Gradient Descent
Tongzheng Ren, Fuheng Cui, Alexia Atsidakou +2
We study the statistical and computational complexities of the Polyak step size gradient descent algorithm under generalized smoothness and Lojasiewicz conditions of the population…
Combinatorial Blocking Bandits with Stochastic Delays
Alexia Atsidakou, Orestis Papadigenopoulos, Soumya Basu +2
Recent work has considered natural variations of the multi-armed bandit problem, where the reward distribution of each arm is a special function of the time passed since its last p…