Optimization

OCD: Learning to Overfit with Conditional Diffusion Models ICML 2023 Offline Model-Based Reinforcement Learning for Tokamak Control L4DC 2023 OKRidge: Scalable Optimal k-Sparse Ridge Regression NeurIPS 2023 OMPQ: Orthogonal Mixed Precision Quantization AAAI 2023 OMS-DPM: Optimizing the Model Schedule for Diffusion Probabilistic Models ICML 2023 On Accelerated Perceptrons and Beyond ICLR 2023 On Adaptivity and Safety in Sequential Decision Making IJCAI 2023 On amortizing convex conjugates for optimal transport ICLR 2023 On Biased Compression for Distributed Learning JMLR 2023 On Calibrating Diffusion Probabilistic Models NeurIPS 2023 On Complementarity Objectives for Hybrid Retrieval ACL 2023 On Computing Optimal Tree Ensembles ICML 2023 On Controller Reduction in Linear Quadratic Gaussian Control with Performance Bounds L4DC 2023 On Coresets for Clustering in Small Dimensional Euclidean spaces ICML 2023 On Dynamic Programming Decompositions of Static Risk Measures in Markov Decision Processes NeurIPS 2023 One-Line-of-Code Data Mollification Improves Optimization of Likelihood-based Generative Models NeurIPS 2023 One Policy is Enough: Parallel Exploration with a Single Policy is Near-Optimal for Reward-Free Reinforcement Learning AISTATS 2023 One-Shot Model for Mixed-Precision Quantization CVPR 2023 One-step differentiation of iterative algorithms NeurIPS 2023 On Generalization of Decentralized Learning with Separable Data AISTATS 2023 On Kinetic Optimal Probability Paths for Generative Models ICML 2023 On Learning Rates and Schrödinger Operators JMLR 2023 Online Ad Allocation with Predictions NeurIPS 2023 Online Ad Procurement in Non-stationary Autobidding Worlds NeurIPS 2023 Online Control for Meta-optimization NeurIPS 2023