20 papers
Beyond Marginal Validity: Finite-Sample Guarantees for Localized Conformal Prediction
Anton Conrad, Rustam Isaev, Denis Belomestny +2
Conformal prediction endows arbitrary black-box predictors with finite-sample, distribution-free marginal coverage, yet marginal validity can hide severe covariate-specific miscali…
Gaussian Approximation and Multiplier Bootstrap for Federated Linear Stochastic Approximation
Ilya Levin, Maksim Shuklin, Eric Moulines +2
In this paper, we establish Berry-Esseen-type bounds for federated linear stochastic approximation (LSA). Our results provide the first federated Gaussian approximations for LSA th…
On Gaussian approximation for entropy-regularized Q-learning with function approximation
Artemy Rubtsov, Rahul Singh, Eric Moulines +2
In this paper, we derive rates of convergence in the high-dimensional central limit theorem for Polyak--Ruppert averaged iterates generated by entropy-regularized asynchronous Q-le…
Gaussian Approximation and Multiplier Bootstrap for Stochastic Gradient Descent
Marina Sheshukova, Sergey Samsonov, Denis Belomestny +4
In this paper, we establish the non-asymptotic validity of the multiplier bootstrap procedure for constructing the confidence sets using the Stochastic Gradient Descent (SGD) algor…
Revisiting the Constant Stepsize Stochastic Approximation with Decision-Dependent Markovian Noise
Hadi Hadavi, Wenlong Mou, Sergey Samsonov +1
We revisit the convergence analysis of constant stepsize stochastic approximation (SA) with decision-dependent Markovian noise, with a focus on characterizing the stationary bias a…
Gaussian Approximation for Asynchronous Q-learning
Artemy Rubtsov, Sergey Samsonov, Vladimir Ulyanov +1
In this paper, we derive rates of convergence in the high-dimensional central limit theorem for Polyak-Ruppert averaged iterates generated by the asynchronous Q-learning algorithm…