6 citations · 17 across the 29 of their papers we have counts for
6 papers · 1 filter
Federated UCBVI: Communication-Efficient Federated Regret Minimization with Heterogeneous Agents
Safwan Labbi, Daniil Tiapkin, Lorenzo Mancini +2
In this paper, we present the Federated Upper Confidence Bound Value Iteration algorithm (), a novel extension of the algorithm (Azar et al., 2…
Optimizing Backward Policies in GFlowNets via Trajectory Likelihood Maximization
Timofei Gritsaev, Nikita Morozov, Sergey Samsonov +1
Generative Flow Networks (GFlowNets) are a family of generative models that learn to sample objects with probabilities proportional to a given reward function. The key concept behi…
A New Bound on the Cumulant Generating Function of Dirichlet Processes
Pierre Perrault, Denis Belomestny, Pierre Ménard +4
In this paper, we introduce a novel approach for bounding the cumulant generating function (CGF) of a Dirichlet process (DP) , using superadditivity. In par…
Narrowing the Gap between Adversarial and Stochastic MDPs via Policy Optimization
Daniil Tiapkin, Evgenii Chzhen, Gilles Stoltz
We consider the problem of learning in adversarial Markov decision processes [MDPs] with an oblivious adversary in a full-information setting. The agent interacts with an environme…
Improving GFlowNets with Monte Carlo Tree Search
Nikita Morozov, Daniil Tiapkin, Sergey Samsonov +2
Generative Flow Networks (GFlowNets) treat sampling from distributions over compositional discrete spaces as a sequential decision-making problem, training a stochastic policy to c…
Incentivized Learning in Principal-Agent Bandit Games
Antoine Scheid, Daniil Tiapkin, Etienne Boursier +5
This work considers a repeated principal-agent bandit game, where the principal can only interact with her environment through the agent. The principal and the agent have misaligne…