6 papers
Refined Analysis of Entropy-Regularized Actor-Critic
Safwan Labbi, Paul Mangold, Daniil Tiapkin +1
In this paper, we study the role of the critic in actor--critic for entropy-regularized, finite, discounted environments. We establish that, when the critic is exact, using the lat…
Beyond Softmax and Entropy: Convergence Rates of Policy Gradients with f-SoftArgmax Parameterization & Coupled Regularization
Safwan Labbi, Daniil Tiapkin, Paul Mangold +1
Policy gradient methods are known to be highly sensitive to the choice of policy parameterization. In particular, the widely used softmax parameterization can induce ill-conditione…
On Global Convergence Rates for Federated Softmax Policy Gradient under Heterogeneous Environments
Safwan Labbi, Paul Mangold, Daniil Tiapkin +1
We provide global convergence rates for vanilla and entropy-regularized federated softmax stochastic policy gradient (FedPG) with local training. We show that FedPG converges to a…
SCAFFLSA: Taming Heterogeneity in Federated Linear Stochastic Approximation and TD Learning
Paul Mangold, Sergey Samsonov, Safwan Labbi +4
In this paper, we analyze the sample and communication complexity of the federated linear stochastic approximation (FedLSA) algorithm. We explicitly quantify the effects of local t…
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…
Joint Channel Selection using FedDRL in V2X
Lorenzo Mancini, Safwan Labbi, Karim Abed Meraim +4
Vehicle-to-everything (V2X) communication technology is revolutionizing transportation by enabling interactions between vehicles, devices, and infrastructures. This connectivity en…