Continuous Optimization

Compression of Structured Data with Autoencoders: Provable Benefit of Nonlinearities and Depth ICML 2024 Computation-Aware Learning for Stable Control with Gaussian Process RSS 2024 Conformal Inverse Optimization NeurIPS 2024 Connectivity Shapes Implicit Regularization in Matrix Factorization Models for Matrix Completion NeurIPS 2024 Consistent Multiclass Algorithms for Complex Metrics and Constraints JMLR 2024 Constant Acceleration Flow NeurIPS 2024 Constrained Binary Decision Making NeurIPS 2024 Constrained Diffusion with Trust Sampling NeurIPS 2024 Constraint-Free Structure Learning with Smooth Acyclic Orientations ICLR 2024 Continuous Partitioning for Graph-Based Semi-Supervised Learning NeurIPS 2024 Contrasting Multiple Representations with the Multi-Marginal Matching Gap ICML 2024 Controlling Continuous Relaxation for Combinatorial Optimization NeurIPS 2024 Control with Patterns: A D-learning Method CoRL 2024 Convergence and Complexity Guarantee for Inexact First-order Riemannian Optimization Algorithms ICML 2024 Convergence and Trade-Offs in Riemannian Gradient Descent and Riemannian Proximal Point ICML 2024 Convergence for nonconvex ADMM, with applications to CT imaging JMLR 2024 Convergence Guarantees for the DeepWalk Embedding on Block Models ICML 2024 Convergence of log(1/ε) for Gradient-Based Algorithms in Zero-Sum Games without the Condition Number: A Smoothed Analysis NeurIPS 2024 Convex approximations for a bi-level formulation of data-enabled predictive control L4DC 2024 Coresets for Multiple ℓ_p Regression ICML 2024 Data-driven robust covariance control for uncertain linear systems L4DC 2024 Data driven verification of positive invariant sets for discrete, nonlinear systems L4DC 2024 Debiasing Evaluations That Are Biased by Evaluations JMLR 2024 Decision-Focused Learning with Directional Gradients NeurIPS 2024 Decision-Making for Land Conservation: A Derivative-Free Optimization Framework with Nonlinear Inputs AAAI 2024