Optimization

TKG-DM: Training-free Chroma Key Content Generation Diffusion Model CVPR 2025 Towards Learning High-Precision Least Squares Algorithms with Sequence Models ICLR 2025 Towards Optimal Evaluation Efficiency for Large Language Models EMNLP 2025 TSDF-Based Efficient Motion-Compensated Temporal Interpolation for 3D Dynamic Sequences AAAI 2025 Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin ICCV 2025 VFOSA: Variance-Reduced Fast Operator Splitting Algorithms for Generalized Equations JMLR 2025 When Extragradient Meets PAGE: Bridging Two Giants to Boost Variational Inequalities UAI 2025 Zeroth-Order Methods for Nonconvex Stochastic Problems with Decision-Dependent Distributions AAAI 2025 Abstract Action Scheduling for Optimal Temporal Planning via OMT AAAI 2024 Accelerating Sinkhorn algorithm with sparse Newton iterations ICLR 2024 Achieving Near-Optimal Convergence for Distributed Minimax Optimization with Adaptive Stepsizes NeurIPS 2024 Achieving Tractable Minimax Optimal Regret in Average Reward MDPs NeurIPS 2024 A Class of Topological Pseudodistances for Fast Comparison of Persistence Diagrams AAAI 2024 Active Learning for Derivative-Based Global Sensitivity Analysis with Gaussian Processes NeurIPS 2024 AdaLomo: Low-memory Optimization with Adaptive Learning Rate ACL 2024 Adaptive and non-adaptive minimax rates for weighted Laplacian-Eigenmap based nonparametric regression AISTATS 2024 Adaptive and Optimal Second-order Optimistic Methods for Minimax Optimization NeurIPS 2024 Adaptive Quasi-Newton and Anderson Acceleration Framework with Explicit Global (Accelerated) Convergence Rates AISTATS 2024 A De-singularity Subgradient Approach for the Extended Weber Location Problem IJCAI 2024 A Discretization Framework for Robust Contextual Stochastic Optimization ICLR 2024 Adjust Pearson's r to Measure Arbitrary Monotone Dependence NeurIPS 2024 Advancing the Lower Bounds: an Accelerated, Stochastic, Second-order Method with Optimal Adaptation to Inexactness ICLR 2024 A Framework for Data-Driven Explainability in Mathematical Optimization AAAI 2024 A Globally Optimal Portfolio for m-Sparse Sharpe Ratio Maximization NeurIPS 2024 Algorithms for mean-field variational inference via polyhedral optimization in the Wasserstein space COLT 2024