Mathematics & Optimization

On the Convergence of No-Regret Learning Dynamics in Time-Varying Games NeurIPS 2023 On the Convergence of Stochastic Gradient Descent with Bandwidth-based Step Size JMLR 2023 On the convergence of the MLE as an estimator of the learning rate in the Exp3 algorithm ICML 2023 On the Convergence Rate of Gaussianization with Random Rotations ICML 2023 On the Convergence to a Global Solution of Shuffling-Type Gradient Algorithms NeurIPS 2023 On the Efficacy of Sampling Adapters ACL 2023 On the Estimation of Derivatives Using Plug-in Kernel Ridge Regression Estimators JMLR 2023 On the Estimation of Gaussian Mixture Copula Models ICML 2023 On the Existence of a Complexity in Fixed Budget Bandit Identification COLT 2023 On the Exploration of Local Significant Differences For Two-Sample Test NeurIPS 2023 On the Generalization Error of Stochastic Mirror Descent for Quadratically-Bounded Losses: an Improved Analysis NeurIPS 2023 On the geometry of Stein variational gradient descent JMLR 2023 On the Interplay Between Misspecification and Sub-optimality Gap in Linear Contextual Bandits ICML 2023 On the Interplay between Social Welfare and Tractability of Equilibria NeurIPS 2023 On the Lower Bound of Minimizing Polyak-Łojasiewicz functions COLT 2023 On the Minimax Regret for Online Learning with Feedback Graphs NeurIPS 2023 On the Optimality of Misspecified Kernel Ridge Regression ICML 2023 On the Optimality of Nuclear-norm-based Matrix Completion for Problems with Smooth Non-linear Structure JMLR 2023 On the Overlooked Structure of Stochastic Gradients NeurIPS 2023 On The Relative Error of Random Fourier Features for Preserving Kernel Distance ICLR 2023 On the Robustness of Mechanism Design under Total Variation Distance NeurIPS 2023 On the Role of Memory in Robust Opinion Dynamics IJCAI 2023 On the role of model uncertainties in Bayesian optimisation UAI 2023 On the Sublinear Regret of GP-UCB NeurIPS 2023 On Unbalanced Optimal Transport: Gradient Methods, Sparsity and Approximation Error JMLR 2023