6 citations · 8 across the 7 of their papers we have counts for
5 papers · 1 filter
Communication-Efficient Collaborative Regret Minimization in Multi-Armed Bandits
Nikolai Karpov, Qin Zhang
In this paper, we study the collaborative learning model, which concerns the tradeoff between parallelism and communication overhead in multi-agent multi-armed bandits. For regret…
Communication-Efficient Collaborative Best Arm Identification
Nikolai Karpov, Qin Zhang
We investigate top- arm identification, a basic problem in bandit theory, in a multi-agent learning model in which agents collaborate to learn an objective function. We are inte…
Parallel Best Arm Identification in Heterogeneous Environments
Nikolai Karpov, Qin Zhang
In this paper, we study the tradeoffs between the time and the number of communication rounds of the best arm identification problem in the heterogeneous collaborative learning mod…
Batched Thompson Sampling for Multi-Armed Bandits
Nikolai Karpov, Qin Zhang
We study Thompson Sampling algorithms for stochastic multi-armed bandits in the batched setting, in which we want to minimize the regret over a sequence of arm pulls using a small…
Instance-Sensitive Algorithms for Pure Exploration in Multinomial Logit Bandit
Nikolai Karpov, Qin Zhang
Motivated by real-world applications such as fast fashion retailing and online advertising, the Multinomial Logit Bandit (MNL-bandit) is a popular model in online learning and oper…