Convex Optimization

Learning with semi-definite programming: statistical bounds based on fixed point analysis and excess risk curvature JMLR 2021 Local Search Algorithms for Rank-Constrained Convex Optimization ICLR 2021 Low-Rank Extragradient Method for Nonsmooth and Low-Rank Matrix Optimization Problems NeurIPS 2021 Low Resource Quadratic Forms for Knowledge Graph Embeddings EMNLP 2021 Oblivious Sketching-based Central Path Method for Linear Programming ICML 2021 On a Combination of Alternating Minimization and Nesterov’s Momentum ICML 2021 Primal-dual Learning for the Model-free Risk-constrained Linear Quadratic Regulator L4DC 2021 Revisiting Projection-free Online Learning: the Strongly Convex Case AISTATS 2021 Semialgebraic Representation of Monotone Deep Equilibrium Models and Applications to Certification NeurIPS 2021 SKFAC: Training Neural Networks With Faster Kronecker-Factored Approximate Curvature CVPR 2021 Smooth Convex Optimization Using Sub-Zeroth-Order Oracles AAAI 2021 Sparse and Smooth Signal Estimation: Convexification of L0-Formulations JMLR 2021 Structured Logconcave Sampling with a Restricted Gaussian Oracle COLT 2021 The Bethe and Sinkhorn Permanents of Low Rank Matrices and Implications for Profile Maximum Likelihood COLT 2021 Thinking Inside the Ball: Near-Optimal Minimization of the Maximal Loss COLT 2021 Three Operator Splitting with a Nonconvex Loss Function ICML 2021 Three Operator Splitting with Subgradients, Stochastic Gradients, and Adaptive Learning Rates NeurIPS 2021 Transforms Based Tensor Robust PCA: Corrupted Low-Rank Tensors Recovery via Convex Optimization ICCV 2021 Unifying Width-Reduced Methods for Quasi-Self-Concordant Optimization NeurIPS 2021 A Catalyst Framework for Minimax Optimization NeurIPS 2020 A Certifiably Globally Optimal Solution to Generalized Essential Matrix Estimation CVPR 2020 A convex optimization formulation for multivariate regression NeurIPS 2020 A Data Efficient and Feasible Level Set Method for Stochastic Convex Optimization with Expectation Constraints JMLR 2020 A Flexible Framework for Designing Trainable Priors with Adaptive Smoothing and Game Encoding NeurIPS 2020 An Õ(m/ε^3.5)-Cost Algorithm for Semidefinite Programs with Diagonal Constraints COLT 2020