convex optimization

Beyond Unfolding: Exact Recovery of Latent Convex Tensor Decomposition Under Reshuffling AAAI 2020 Boosting First-Order Methods by Shifting Objective: New Schemes with Faster Worst-Case Rates NeurIPS 2020 Comparator-Adaptive Convex Bandits NeurIPS 2020 Conditional gradient methods for stochastically constrained convex minimization ICML 2020 Convergence Analysis of Block Coordinate Algorithms with Determinantal Sampling AISTATS 2020 Convex and Non-Convex Approaches for Statistical Inference with Class-Conditional Noisy Labels JMLR 2020 Convex Geometry of Two-Layer ReLU Networks: Implicit Autoencoding and Interpretable Models AISTATS 2020 Convex optimization based on global lower second-order models NeurIPS 2020 Costly Zero Order Oracles COLT 2020 Delay-Adaptive Distributed Stochastic Optimization AAAI 2020 Dimension-Free Bounds for Chasing Convex Functions COLT 2020 Discerning the Linear Convergence of ADMM for Structured Convex Optimization through the Lens of Variational Analysis JMLR 2020 Distributionally Ambiguous Optimization for Batch Bayesian Optimization JMLR 2020 Distributionally Robust Local Non-parametric Conditional Estimation NeurIPS 2020 Do Subsampled Newton Methods Work for High-Dimensional Data? AAAI 2020 Dual Instrumental Variable Regression NeurIPS 2020 Dynamic Regret of Convex and Smooth Functions NeurIPS 2020 Efficient Proximal Mapping of the 1-path-norm of Shallow Networks ICML 2020 EiGLasso: Scalable Estimation of Cartesian Product of Sparse Inverse Covariance Matrices UAI 2020 Estimating Reachable Sets with Scenario Optimization L4DC 2020 Exploiting Model Sparsity in Adaptive MPC: A Compressed Sensing Viewpoint L4DC 2020 Fenchel Lifted Networks: A Lagrange Relaxation of Neural Network Training AISTATS 2020 Fine-Grained Analysis of Stability and Generalization for Stochastic Gradient Descent ICML 2020 First-Order Methods for Large-Scale Market Equilibrium Computation NeurIPS 2020 Fixed-Support Wasserstein Barycenters: Computational Hardness and Fast Algorithm NeurIPS 2020