conftrace_

linear convergence

158 papers

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Co-occurring keywords

convex optimization (1321) gradient descent (1144) stochastic optimization (1060) variance reduction (523) stochastic gradient (296) stochastic gradient descent (1091) strong convexity (59) frank-wolfe algorithm (107) coordinate descent (147) support vector machine (978)

Papers

Towards Practical Alternating Least-Squares for CCA NIPS 2019
Parallel Asynchronous Stochastic Coordinate Descent with Auxiliary Variables AISTATS 2019
Blended Conditonal Gradients ICML 2019
A Quantitative Analysis of the Effect of Batch Normalization on Gradient Descent ICML 2019
Accelerated Linear Convergence of Stochastic Momentum Methods in Wasserstein Distances ICML 2019
SAGA with Arbitrary Sampling ICML 2019
A unified variance-reduced accelerated gradient method for convex optimization NIPS 2019
Finite-Time Performance Bounds and Adaptive Learning Rate Selection for Two Time-Scale Reinforcement Learning NIPS 2019
Stochastic Variance Reduced Primal Dual Algorithms for Empirical Composition Optimization NIPS 2019
General Proximal Incremental Aggregated Gradient Algorithms: Better and Novel Results under General Scheme NIPS 2019
Non-Ergodic Convergence Analysis of Heavy-Ball Algorithms AAAI 2019
Iterative Least Trimmed Squares for Mixed Linear Regression NIPS 2019
Primal-Dual Block Generalized Frank-Wolfe NIPS 2019
Linear Convergence of the Primal-Dual Gradient Method for Convex-Concave Saddle Point Problems without Strong Convexity AISTATS 2019
Restarting Frank-Wolfe AISTATS 2019
Theoretical Linear Convergence of Unfolded ISTA and Its Practical Weights and Thresholds NIPS 2018
A Delay-tolerant Proximal-Gradient Algorithm for Distributed Learning ICML 2018
Convergence Analysis of Gradient Descent for Eigenvector Computation IJCAI 2018
Stochastic Spectral and Conjugate Descent Methods NIPS 2018
A Simple Proximal Stochastic Gradient Method for Nonsmooth Nonconvex Optimization NIPS 2018
Proximal SCOPE for Distributed Sparse Learning NIPS 2018
Limited Memory Kelley's Method Converges for Composite Convex and Submodular Objectives NIPS 2018
Towards Memory-Friendly Deterministic Incremental Gradient Method AISTATS 2018
Towards Provable Learning of Polynomial Neural Networks Using Low-Rank Matrix Estimation AISTATS 2018
Guaranteed Sufficient Decrease for Stochastic Variance Reduced Gradient Optimization AISTATS 2018