convex optimization

Inference for probabilistic dependency graphs UAI 2023 Is Consensus Acceleration Possible in Decentralized Optimization over Slowly Time-Varying Networks? ICML 2023 Iteratively Enhanced Semidefinite Relaxations for Efficient Neural Network Verification AAAI 2023 Learning-Rate-Free Learning by D-Adaptation ICML 2023 Learning the Efficient Frontier NeurIPS 2023 LegendreTron: Uprising Proper Multiclass Loss Learning ICML 2023 Levin Tree Search with Context Models IJCAI 2023 Linearization Algorithms for Fully Composite Optimization COLT 2023 Lower Bounds and Accelerated Algorithms for Bilevel Optimization JMLR 2023 Memory-Constrained Algorithms for Convex Optimization NeurIPS 2023 Mirror Sinkhorn: Fast Online Optimization on Transport Polytopes ICML 2023 Mixture Weight Estimation and Model Prediction in Multi-source Multi-target Domain Adaptation NeurIPS 2023 Non-Euclidean Motion Planning with Graphs of Geodesically-Convex Sets RSS 2023 Online Linearized LASSO AISTATS 2023 On Solution Functions of Optimization: Universal Approximation and Covering Number Bounds AAAI 2023 On the Convergence of AdaGrad(Norm) on R^d: Beyond Convexity, Non-Asymptotic Rate and Acceleration ICLR 2023 Open Problem: Polynomial linearly-convergent method for g-convex optimization? COLT 2023 Optimal Guarantees for Algorithmic Reproducibility and Gradient Complexity in Convex Optimization NeurIPS 2023 Optimal Sets and Solution Paths of ReLU Networks ICML 2023 Parallel Deep Neural Networks Have Zero Duality Gap ICLR 2023 Path Regularization: A Convexity and Sparsity Inducing Regularization for Parallel ReLU Networks NeurIPS 2023 Policy-Based Primal-Dual Methods for Convex Constrained Markov Decision Processes AAAI 2023 Polynomial Preconditioning for Gradient Methods ICML 2023 Predictive Multiplicity in Probabilistic Classification AAAI 2023 Private Federated Learning Without a Trusted Server: Optimal Algorithms for Convex Losses ICLR 2023