conftrace_

convergence rate

607 papers

Explore in graph

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

Affine Invariant Analysis of Frank-Wolfe on Strongly Convex Sets ICML 2021
Stability and Convergence of Stochastic Gradient Clipping: Beyond Lipschitz Continuity and Smoothness ICML 2021
Loop Estimator for Discounted Values in Markov Reward Processes AAAI 2021
On Convergence of Nearest Neighbor Classifiers over Feature Transformations NIPS 2020
Proximal Gradient Algorithm with Momentum and Flexible Parameter Restart for Nonconvex Optimization IJCAI 2020
Accelerating Stratified Sampling SGD by Reconstructing Strata IJCAI 2020
Convergences of Regularized Algorithms and Stochastic Gradient Methods with Random Projections JMLR 2020
Fast Rates for General Unbounded Loss Functions: From ERM to Generalized Bayes JMLR 2020
On Stationary-Point Hitting Time and Ergodicity of Stochastic Gradient Langevin Dynamics JMLR 2020
Convergence Rate of Optimal Quantization and Application to the Clustering Performance of the Empirical Measure JMLR 2020
Convergence Rates for the Stochastic Gradient Descent Method for Non-Convex Objective Functions JMLR 2020
AdaGrad stepsizes: Sharp convergence over nonconvex landscapes JMLR 2020
Theory of Curriculum Learning, with Convex Loss Functions JMLR 2020
The Error-Feedback framework: SGD with Delayed Gradients JMLR 2020
Finite-Time Performance of Distributed Two-Time-Scale Stochastic Approximation L4DC 2020
A Finite-Time Analysis of Q-Learning with Neural Network Function Approximation ICML 2020
Generative Adversarial Imitation Learning with Neural Network Parameterization: Global Optimality and Convergence Rate ICML 2020
Convergence Rates of Variational Inference in Sparse Deep Learning ICML 2020
Manifold Identification for Ultimately Communication-Efficient Distributed Optimization ICML 2020
Optimal Randomized First-Order Methods for Least-Squares Problems ICML 2020
SPAN: A Stochastic Projected Approximate Newton Method AAAI 2020
Tight Convergence Rate of Gradient Descent for Eigenvalue Computation IJCAI 2020
Explicit Mean-Square Error Bounds for Monte-Carlo and Linear Stochastic Approximation AISTATS 2020
Stochastic Gradient and Langevin Processes ICML 2020
D-SPIDER-SFO: A Decentralized Optimization Algorithm with Faster Convergence Rate for Nonconvex Problems AAAI 2020