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Convex Optimization

589 directly classified papers

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Papers

Provable Convex Co-clustering of Tensors JMLR 2020
A Certifiably Globally Optimal Solution to Generalized Essential Matrix Estimation CVPR 2020
A Data Efficient and Feasible Level Set Method for Stochastic Convex Optimization with Expectation Constraints JMLR 2020
Stochastic Conditional Gradient Methods: From Convex Minimization to Submodular Maximization JMLR 2020
Learning with Fenchel-Young losses JMLR 2020
Minimizing Discrete Total Curvature for Image Processing CVPR 2020
On the Complexity Analysis of the Primal Solutions for the Accelerated Randomized Dual Coordinate Ascent JMLR 2020
Improved Algorithms for Convex-Concave Minimax Optimization NIPS 2020
Learning Structured Distributions From Untrusted Batches: Faster and Simpler NIPS 2020
Conic Optimization for Quadratic Regression Under Sparse Noise JMLR 2020
A Catalyst Framework for Minimax Optimization NIPS 2020
Relative Interior Rule in Block-Coordinate Descent CVPR 2020
A Unified Optimization Framework for Low-Rank Inducing Penalties CVPR 2020
Robust Policy Synthesis for Uncertain POMDPs via Convex Optimization IJCAI 2020
Plug-and-Play Algorithms for Large-Scale Snapshot Compressive Imaging CVPR 2020
Learning Composable Energy Surrogates for PDE Order Reduction NIPS 2020
Proximity Operator of the Matrix Perspective Function and its Applications NIPS 2020
Hard Shape-Constrained Kernel Machines NIPS 2020
A Simple and Efficient Smoothing Method for Faster Optimization and Local Exploration NIPS 2020
Better Full-Matrix Regret via Parameter-Free Online Learning NIPS 2020
Linear Convergence of Randomized Primal-Dual Coordinate Method for Large-scale Linear Constrained Convex Programming ICML 2020
Fenchel Lifted Networks: A Lagrange Relaxation of Neural Network Training AISTATS 2020
A convex optimization formulation for multivariate regression NIPS 2020
Random Reshuffling: Simple Analysis with Vast Improvements NIPS 2020
Distributed Newton Can Communicate Less and Resist Byzantine Workers NIPS 2020