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

Lower Bounds on Metropolized Sampling Methods for Well-Conditioned Distributions NIPS 2021
Near Optimal Policy Optimization via REPS NIPS 2021
Convergence Rates of Stochastic Gradient Descent under Infinite Noise Variance NIPS 2021
Frugal Optimization for Cost-related Hyperparameters AAAI 2021
On a Combination of Alternating Minimization and Nesterov’s Momentum ICML 2021
GBHT: Gradient Boosting Histogram Transform for Density Estimation ICML 2021
An Analysis of the Adaptation Speed of Causal Models AISTATS 2021
Improved Penalty Method via Doubly Stochastic Gradients for Bilevel Hyperparameter Optimization AAAI 2021
Sifting through the noise: Universal first-order methods for stochastic variational inequalities NIPS 2021
Preconditioned Gradient Descent for Over-Parameterized Nonconvex Matrix Factorization NIPS 2021
EF21: A New, Simpler, Theoretically Better, and Practically Faster Error Feedback NIPS 2021
CANITA: Faster Rates for Distributed Convex Optimization with Communication Compression NIPS 2021
Simple steps are all you need: Frank-Wolfe and generalized self-concordant functions NIPS 2021
Stability and Deviation Optimal Risk Bounds with Convergence Rate $O(1/n)$ NIPS 2021
The Last-Iterate Convergence Rate of Optimistic Mirror Descent in Stochastic Variational Inequalities COLT 2021
On the Convergence of Step Decay Step-Size for Stochastic Optimization NIPS 2021
Newton-LESS: Sparsification without Trade-offs for the Sketched Newton Update NIPS 2021
An Improved Analysis of Gradient Tracking for Decentralized Machine Learning NIPS 2021
Nonlinear Two-Time-Scale Stochastic Approximation: Convergence and Finite-Time Performance L4DC 2021
An Improved Analysis and Rates for Variance Reduction under Without-replacement Sampling Orders NIPS 2021
A Comprehensively Tight Analysis of Gradient Descent for PCA NIPS 2021
A Modular Analysis of Provable Acceleration via Polyak’s Momentum: Training a Wide ReLU Network and a Deep Linear Network ICML 2021
How Well Generative Adversarial Networks Learn Distributions JMLR 2021
SMG: A Shuffling Gradient-Based Method with Momentum ICML 2021
Differentiating the Value Function by using Convex Duality AISTATS 2021