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Optimization

14,983 papers

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Papers

A General System of Differential Equations to Model First-Order Adaptive Algorithms JMLR 2020
Gradient Descent for Sparse Rank-One Matrix Completion for Crowd-Sourced Aggregation of Sparsely Interacting Workers JMLR 2020
Convergence Rates for the Stochastic Gradient Descent Method for Non-Convex Objective Functions JMLR 2020
A Data Efficient and Feasible Level Set Method for Stochastic Convex Optimization with Expectation Constraints JMLR 2020
Orlicz Random Fourier Features JMLR 2020
New Insights and Perspectives on the Natural Gradient Method JMLR 2020
Optimal Convergence for Distributed Learning with Stochastic Gradient Methods and Spectral Algorithms JMLR 2020
Dual Iterative Hard Thresholding JMLR 2020
Estimate Sequences for Stochastic Composite Optimization: Variance Reduction, Acceleration, and Robustness to Noise JMLR 2020
Generating Weighted MAX-2-SAT Instances with Frustrated Loops: an RBM Case Study JMLR 2020
Trust-Region Variational Inference with Gaussian Mixture Models JMLR 2020
High Dimensional Forecasting via Interpretable Vector Autoregression JMLR 2020
The Optimal Ridge Penalty for Real-world High-dimensional Data Can Be Zero or Negative due to the Implicit Ridge Regularization JMLR 2020
Krylov Subspace Method for Nonlinear Dynamical Systems with Random Noise JMLR 2020
Communication-Efficient Distributed Optimization in Networks with Gradient Tracking and Variance Reduction JMLR 2020
Consistency of Semi-Supervised Learning Algorithms on Graphs: Probit and One-Hot Methods JMLR 2020
Adaptive Smoothing for Path Integral Control JMLR 2020
Conic Optimization for Quadratic Regression Under Sparse Noise JMLR 2020
Empirical Risk Minimization in the Non-interactive Local Model of Differential Privacy JMLR 2020
On Convergence of Distributed Approximate Newton Methods: Globalization, Sharper Bounds and Beyond JMLR 2020
Learning Data-adaptive Non-parametric Kernels JMLR 2020
Provable Convex Co-clustering of Tensors JMLR 2020
AdaGrad stepsizes: Sharp convergence over nonconvex landscapes JMLR 2020
Theory of Curriculum Learning, with Convex Loss Functions JMLR 2020
A Sparse Semismooth Newton Based Proximal Majorization-Minimization Algorithm for Nonconvex Square-Root-Loss Regression Problems JMLR 2020