Convex Optimization

Learning (from) Deep Hierarchical Structure among Features AAAI 2019 Learning Positive Functions with Pseudo Mirror Descent NeurIPS 2019 Learning Weighted Top-k Support Vector Machine ACML 2019 Lifted Hinge-Loss Markov Random Fields AAAI 2019 Lifting Vectorial Variational Problems: A Natural Formulation Based on Geometric Measure Theory and Discrete Exterior Calculus CVPR 2019 Lipschitz Adaptivity with Multiple Learning Rates in Online Learning COLT 2019 Lower Bounds for Parallel and Randomized Convex Optimization COLT 2019 Low-Rank Tensor Completion With a New Tensor Nuclear Norm Induced by Invertible Linear Transforms CVPR 2019 Maximum Entropy Distributions: Bit Complexity and Stability COLT 2019 Minimum Volume Topic Modeling AISTATS 2019 Multi-Criteria Dimensionality Reduction with Applications to Fairness NeurIPS 2019 Non-Convex Matrix Completion and Related Problems via Strong Duality JMLR 2019 Online Convex Matrix Factorization with Representative Regions NeurIPS 2019 On Sampling Complexity of the Semidefinite Affine Rank Feasibility Problem AAAI 2019 On the Curved Geometry of Accelerated Optimization NeurIPS 2019 Open Problem: Do Good Algorithms Necessarily Query Bad Points? COLT 2019 Open Problem: The Oracle Complexity of Convex Optimization with Limited Memory COLT 2019 Optimization of Inf-Convolution Regularized Nonconvex Composite Problems AISTATS 2019 Outlier Detection and Robust PCA Using a Convex Measure of Innovation NeurIPS 2019 Primal-Dual Block Generalized Frank-Wolfe NeurIPS 2019 Radial Distortion Triangulation CVPR 2019 Relative Error Bound Analysis for Nuclear Norm Regularized Matrix Completion JMLR 2019 Solving Empirical Risk Minimization in the Current Matrix Multiplication Time COLT 2019 Solving the OSCAR and SLOPE Models Using a Semismooth Newton-Based Augmented Lagrangian Method JMLR 2019 Stochastic Approximation of Smooth and Strongly Convex Functions: Beyond the $O(1/T)$ Convergence Rate COLT 2019