conftrace_

convergence rate

607 papers

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Co-occurring keywords

stochastic gradient descent (1091) convex optimization (1321) stochastic optimization (1060) gradient descent (1144) convergence analysis (395) non-convex optimization (547) nonconvex optimization (316) variance reduction (523) stochastic gradient (296) learning theory (519)

Papers

Efficient MCMC Sampling with Dimension-Free Convergence Rate using ADMM-type Splitting JMLR 2022
Trajectory of Mini-Batch Momentum: Batch Size Saturation and Convergence in High Dimensions NIPS 2022
Pairwise Conditional Gradients without Swap Steps and Sparser Kernel Herding ICML 2022
Correlated Quantization for Distributed Mean Estimation and Optimization ICML 2022
Continuous-Time Analysis of Accelerated Gradient Methods via Conservation Laws in Dilated Coordinate Systems ICML 2022
Constants Matter: The Performance Gains of Active Learning ICML 2022
Refined Convergence Rates for Maximum Likelihood Estimation under Finite Mixture Models ICML 2022
Kill a Bird with Two Stones: Closing the Convergence Gaps in Non-Strongly Convex Optimization by Directly Accelerated SVRG with Double Compensation and Snapshots ICML 2022
On Convergence of Gradient Descent Ascent: A Tight Local Analysis ICML 2022
Provable Tensor-Train Format Tensor Completion by Riemannian Optimization JMLR 2022
Gradient Descent Is Optimal Under Lower Restricted Secant Inequality And Upper Error Bound NIPS 2022
The EM Algorithm is Adaptively-Optimal for Unbalanced Symmetric Gaussian Mixtures JMLR 2022
Convergence Guarantees for the Good-Turing Estimator JMLR 2022
Optimistic Tree Searches for Combinatorial Black-Box Optimization NIPS 2022
On the Convergence Rates of Policy Gradient Methods JMLR 2022
On Non-local Convergence Analysis of Deep Linear Networks ICML 2022
Theoretical Convergence of Multi-Step Model-Agnostic Meta-Learning JMLR 2022
Convergence Rates of Non-Convex Stochastic Gradient Descent Under a Generic Lojasiewicz Condition and Local Smoothness ICML 2022
Revisiting Optimal Convergence Rate for Smooth and Non-convex Stochastic Decentralized Optimization NIPS 2022
Gaussian process regression: Optimality, robustness, and relationship with kernel ridge regression JMLR 2022
Whitening Convergence Rate of Coupling-based Normalizing Flows NIPS 2022
Improved Convergence Rates for Sparse Approximation Methods in Kernel-Based Learning ICML 2022
Nesterov Accelerated Shuffling Gradient Method for Convex Optimization ICML 2022
Anarchic Federated Learning ICML 2022
DPCD: Discrete Principal Coordinate Descent for Binary Variable Problems AAAI 2022