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

Revisiting Optimal Convergence Rate for Smooth and Non-convex Stochastic Decentralized Optimization NIPS 2022
Approaching Quartic Convergence Rates for Quasi-Stochastic Approximation with Application to Gradient-Free Optimization NIPS 2022
Deep Architecture Connectivity Matters for Its Convergence: A Fine-Grained Analysis NIPS 2022
Approximate Frank-Wolfe Algorithms over Graph-structured Support Sets ICML 2022
Anchor-Changing Regularized Natural Policy Gradient for Multi-Objective Reinforcement Learning NIPS 2022
On Non-local Convergence Analysis of Deep Linear Networks ICML 2022
Revisit last-iterate convergence of mSGD under milder requirement on step size NIPS 2022
On the Convergence Rates of Policy Gradient Methods JMLR 2022
On the Convergence of Stochastic Extragradient for Bilinear Games using Restarted Iteration Averaging AISTATS 2022
Towards Noise-adaptive, Problem-adaptive (Accelerated) Stochastic Gradient Descent ICML 2022
Sharpened Quasi-Newton Methods: Faster Superlinear Rate and Larger Local Convergence Neighborhood ICML 2022
Faster Single-loop Algorithms for Minimax Optimization without Strong Concavity AISTATS 2022
HNO: High-Order Numerical Architecture for ODE-Inspired Deep Unfolding Networks AAAI 2022
Convex Analysis of the Mean Field Langevin Dynamics AISTATS 2022
Beyond the Policy Gradient Theorem for Efficient Policy Updates in Actor-Critic Algorithms AISTATS 2022
Understanding and mitigating the limitations of prioritized experience replay UAI 2022
Multi-class classification in nonparametric active learning AISTATS 2022
Near-optimal Local Convergence of Alternating Gradient Descent-Ascent for Minimax Optimization AISTATS 2022
State Dependent Performative Prediction with Stochastic Approximation AISTATS 2022
Gaussian process regression: Optimality, robustness, and relationship with kernel ridge regression JMLR 2022
Towards Statistical and Computational Complexities of Polyak Step Size Gradient Descent AISTATS 2022
Semi-Implicit Hybrid Gradient Methods with Application to Adversarial Robustness AISTATS 2022
Super-Acceleration with Cyclical Step-sizes AISTATS 2022
Stochastic Extragradient: General Analysis and Improved Rates AISTATS 2022
DPCD: Discrete Principal Coordinate Descent for Binary Variable Problems AAAI 2022