Optimization

1-Lipschitz Layers Compared: Memory Speed and Certifiable Robustness CVPR 2024 3D Structure Prediction of Atomic Systems with Flow-based Direct Preference Optimization NeurIPS 2024 4-bit Shampoo for Memory-Efficient Network Training NeurIPS 2024 A Bias-Free Revenue-Maximizing Bidding Strategy for Data Consumers in Auction-based Federated Learning IJCAI 2024 A Boosting-Type Convergence Result for AdaBoost.MH with Factorized Multi-Class Classifiers NeurIPS 2024 A Bregman Proximal Stochastic Gradient Method with Extrapolation for Nonconvex Nonsmooth Problems AAAI 2024 Absence of spurious solutions far from ground truth: A low-rank analysis with high-order losses AISTATS 2024 Abstract Action Scheduling for Optimal Temporal Planning via OMT AAAI 2024 A/B Testing and Best-arm Identification for Linear Bandits with Robustness to Non-stationarity AISTATS 2024 A Call for Clarity in Beam Search: How It Works and When It Stops COLING 2024 Accelerated Algorithms for Constrained Nonconvex-Nonconcave Min-Max Optimization and Comonotone Inclusion ICML 2024 Accelerated Convergence of Stochastic Heavy Ball Method under Anisotropic Gradient Noise ICLR 2024 Accelerated Gradient Tracking over Time-varying Graphs for Decentralized Optimization JMLR 2024 Accelerated Parameter-Free Stochastic Optimization COLT 2024 Accelerated Policy Gradient for s-rectangular Robust MDPs with Large State Spaces ICML 2024 Accelerated Policy Gradient: On the Convergence Rates of the Nesterov Momentum for Reinforcement Learning ICML 2024 Accelerated Regularized Learning in Finite N-Person Games NeurIPS 2024 Accelerating Adversarially Robust Model Selection for Deep Neural Networks via Racing AAAI 2024 Accelerating Data Generation for Neural Operators via Krylov Subspace Recycling ICLR 2024 Accelerating Diffusion Sampling with Optimized Time Steps CVPR 2024 Accelerating ERM for data-driven algorithm design using output-sensitive techniques NeurIPS 2024 Accelerating Greedy Coordinate Gradient and General Prompt Optimization via Probe Sampling NeurIPS 2024 Accelerating Heterogeneous Federated Learning with Closed-form Classifiers ICML 2024 Accelerating Legacy Numerical Solvers by Non-intrusive Gradient-based Meta-solving ICML 2024 Accelerating Non-Maximum Suppression: A Graph Theory Perspective NeurIPS 2024