convergence rate

Pairwise Conditional Gradients without Swap Steps and Sparser Kernel Herding ICML 2022 Permutation-Based SGD: Is Random Optimal? ICLR 2022 PipeGCN: Efficient Full-Graph Training of Graph Convolutional Networks with Pipelined Feature Communication ICLR 2022 Provable Tensor-Train Format Tensor Completion by Riemannian Optimization JMLR 2022 Randomized Stochastic Gradient Descent Ascent AISTATS 2022 Rate of Convergence of Polynomial Networks to Gaussian Processes COLT 2022 Refined Convergence Rates for Maximum Likelihood Estimation under Finite Mixture Models ICML 2022 Revisiting Optimal Convergence Rate for Smooth and Non-convex Stochastic Decentralized Optimization NeurIPS 2022 Revisit last-iterate convergence of mSGD under milder requirement on step size NeurIPS 2022 Sampling without Replacement Leads to Faster Rates in Finite-Sum Minimax Optimization NeurIPS 2022 Semi-Implicit Hybrid Gradient Methods with Application to Adversarial Robustness AISTATS 2022 Sharpened Quasi-Newton Methods: Faster Superlinear Rate and Larger Local Convergence Neighborhood ICML 2022 Sharper Convergence Guarantees for Asynchronous SGD for Distributed and Federated Learning NeurIPS 2022 Single Loop Gaussian Homotopy Method for Non-convex Optimization NeurIPS 2022 State Dependent Performative Prediction with Stochastic Approximation AISTATS 2022 Statistical Rates of Convergence for Functional Partially Linear Support Vector Machines for Classification JMLR 2022 Statistical, Robustness, and Computational Guarantees for Sliced Wasserstein Distances NeurIPS 2022 Stochastic Extragradient: General Analysis and Improved Rates AISTATS 2022 Stochastic subgradient for composite convex optimization with functional constraints JMLR 2022 Super-Acceleration with Cyclical Step-sizes AISTATS 2022 The Curse of Unrolling: Rate of Differentiating Through Optimization NeurIPS 2022 The EM Algorithm is Adaptively-Optimal for Unbalanced Symmetric Gaussian Mixtures JMLR 2022 Theoretical Convergence of Multi-Step Model-Agnostic Meta-Learning JMLR 2022 The Power of Adaptivity in SGD: Self-Tuning Step Sizes with Unbounded Gradients and Affine Variance COLT 2022 Towards Noise-adaptive, Problem-adaptive (Accelerated) Stochastic Gradient Descent ICML 2022