convergence rate

A view of mini-batch SGD via generating functions: conditions of convergence, phase transitions, benefit from negative momenta. ICLR 2023 Beyond Uniform Smoothness: A Stopped Analysis of Adaptive SGD COLT 2023 Communication-efficient Federated Learning with Single-Step Synthetic Features Compressor for Faster Convergence ICCV 2023 Complex-valued Neurons Can Learn More but Slower than Real-valued Neurons via Gradient Descent NeurIPS 2023 Continuous-time Analysis of Anchor Acceleration NeurIPS 2023 Convergence analysis of ODE models for accelerated first-order methods via positive semidefinite kernels NeurIPS 2023 Convergence of First-Order Methods for Constrained Nonconvex Optimization with Dependent Data ICML 2023 Convergence of Proximal Point and Extragradient-Based Methods Beyond Monotonicity: the Case of Negative Comonotonicity ICML 2023 Convergence Rates of a Class of Multivariate Density Estimation Methods Based on Adaptive Partitioning JMLR 2023 Convex and Non-convex Optimization Under Generalized Smoothness NeurIPS 2023 Coordinate Descent Methods for Fractional Minimization ICML 2023 Coordinating Distributed Example Orders for Provably Accelerated Training NeurIPS 2023 Demystifying Softmax Gating Function in Gaussian Mixture of Experts NeurIPS 2023 Don't be so Monotone: Relaxing Stochastic Line Search in Over-Parameterized Models NeurIPS 2023 Dynamic Regularized Sharpness Aware Minimization in Federated Learning: Approaching Global Consistency and Smooth Landscape ICML 2023 Exponential Lower Bounds for Fictitious Play in Potential Games NeurIPS 2023 Extrapolated Random Tree for Regression ICML 2023 Fast Convergence in Learning Two-Layer Neural Networks with Separable Data AAAI 2023 Faster Rates of Convergence to Stationary Points in Differentially Private Optimization ICML 2023 Fast Objective & Duality Gap Convergence for Non-Convex Strongly-Concave Min-Max Problems with PL Condition JMLR 2023 FedBR: Improving Federated Learning on Heterogeneous Data via Local Learning Bias Reduction ICML 2023 Fed-CBS: A Heterogeneity-Aware Client Sampling Mechanism for Federated Learning via Class-Imbalance Reduction ICML 2023 HeteRSGD: Tackling Heterogeneous Sampling Costs via Optimal Reweighted Stochastic Gradient Descent AISTATS 2023 High Probability Bounds for Stochastic Continuous Submodular Maximization AISTATS 2023 High Probability Convergence of Stochastic Gradient Methods ICML 2023