stochastic gradient

Accelerating Relative Entropy Coding with Space Partitioning NeurIPS 2024 Adaptive Stochastic Gradient Algorithm for Black-box Multi-Objective Learning ICLR 2024 autoMALA: Locally adaptive Metropolis-adjusted Langevin algorithm AISTATS 2024 Auto-Train-Once: Controller Network Guided Automatic Network Pruning from Scratch CVPR 2024 B-ary Tree Push-Pull Method is Provably Efficient for Distributed Learning on Heterogeneous Data NeurIPS 2024 Bilevel Optimization under Unbounded Smoothness: A New Algorithm and Convergence Analysis ICLR 2024 Byzantine Robustness and Partial Participation Can Be Achieved at Once: Just Clip Gradient Differences NeurIPS 2024 Compressed and distributed least-squares regression: convergence rates with applications to federated learning JMLR 2024 Discerning Temporal Difference Learning AAAI 2024 Efficient Backpropagation with Variance Controlled Adaptive Sampling ICLR 2024 Fast two-time-scale stochastic gradient method with applications in reinforcement learning COLT 2024 Freya PAGE: First Optimal Time Complexity for Large-Scale Nonconvex Finite-Sum Optimization with Heterogeneous Asynchronous Computations NeurIPS 2024 Improving the Worst-Case Bidirectional Communication Complexity for Nonconvex Distributed Optimization under Function Similarity NeurIPS 2024 Independent Learning in Constrained Markov Potential Games AISTATS 2024 Learning Macroscopic Dynamics from Partial Microscopic Observations NeurIPS 2024 Near-Optimal Distributed Minimax Optimization under the Second-Order Similarity NeurIPS 2024 Nesterov acceleration despite very noisy gradients NeurIPS 2024 Online Composite Optimization Between Stochastic and Adversarial Environments NeurIPS 2024 On Penalty Methods for Nonconvex Bilevel Optimization and First-Order Stochastic Approximation ICLR 2024 On the Convergence of Hierarchical Federated Learning with Partial Worker Participation UAI 2024 On Unbiased Estimation for Partially Observed Diffusions JMLR 2024 Penalized Overdamped and Underdamped Langevin Monte Carlo Algorithms for Constrained Sampling JMLR 2024 PrivSGP-VR: Differentially Private Variance-Reduced Stochastic Gradient Push with Tight Utility Bounds IJCAI 2024 PROMISE: Preconditioned Stochastic Optimization Methods by Incorporating Scalable Curvature Estimates JMLR 2024 Provably Faster Algorithms for Bilevel Optimization via Without-Replacement Sampling NeurIPS 2024