Stochastic Methods

Accelerating Constrained Sampling: A Large Deviations Approach JMLR 2026 A Mean-Field Analysis of Neural Stochastic Gradient Descent-Ascent for Functional Minimax Optimization JMLR 2026 A Single Stepsize Suffices for Unprojected Linear TD(0): Simultaneous Robust and Fast Rates via Polyak–Ruppert Averaging COLT 2026 Asymptotics of Stochastic Gradient Descent with Dropout Regularization in Linear Models JMLR 2026 Bandit Learning in Housing Markets AAAI 2026 Cheap Bootstrap for Fast Uncertainty Quantification of Stochastic Gradient Descent JMLR 2026 Clipping the Price of Adaptivity at the Tail COLT 2026 Departures: Distributional Transport for Single-Cell Perturbation Prediction with Neural Schrödinger Bridges AAAI 2026 Eventually LIL Regret: Almost Sure $\ln\ln T$ Regret for a sub-Gaussian Mixture on Unbounded Data ALT 2026 Fairness Uncertainty Quantification: A Constrained Stochastic Optimization Perspective UAI 2026 Fast and Large-Scale Unbalanced Optimal Transport via its Semi-Dual and Adaptive Gradient Methods COLT 2026 Finite-Time Decoupled Convergence in Nonlinear Two-Time-Scale Stochastic Approximation JMLR 2026 Gaussian Approximation and Multiplier Bootstrap for Federated Linear Stochastic Approximation UAI 2026 High-Accuracy Log-Concave Sampling with Stochastic Queries COLT 2026 Last-Iterate Convergence of Randomized Kaczmarz and SGD with Greedy Step Size COLT 2026 Leveraging Sparsity for Privacy in Collaborative Inference WACV 2026 Limitations of SGD for Multi-Index Models Beyond Statistical Queries COLT 2026 Markovian Compression: Looking to the Past Helps Accelerate the Future UAI 2026 Nearly Linear-Time User-Level DP-SCO with Optimal Rates COLT 2026 On-Average Stability of Multipass Preconditioned SGD and Effective Dimension COLT 2026 Online Convex Optimization with Heavy Tails: Old Algorithms, New Regrets, and Applications ALT 2026 On the Stability of Nonlinear Dynamics in GD and SGD: Beyond Quadratic Potentials COLT 2026 Quantitative Convergence Analysis of Projected Stochastic Gradient Descent for Non-Convex Losses via the Goldstein Subdifferential ALT 2026 Reusing Samples in Variance Reduction ALT 2026 Stochastic Differential Equations models for Least-Squares Stochastic Gradient Descent JMLR 2026