Continuous Optimization

Learning Neural Contracting Dynamics: Extended Linearization and Global Guarantees NeurIPS 2024 Learning Pseudo-Contractive Denoisers for Inverse Problems ICML 2024 Learning-Rate-Free Stochastic Optimization over Riemannian Manifolds ICML 2024 Learning Reduced Fluid Dynamics AAAI 2024 Learning Surrogates for Offline Black-Box Optimization via Gradient Matching ICML 2024 Learning the Uncertainty Sets of Linear Control Systems via Set Membership: A Non-asymptotic Analysis ICML 2024 Learning to Scale Logits for Temperature-Conditional GFlowNets ICML 2024 Learning to Warm-Start Fixed-Point Optimization Algorithms JMLR 2024 Learning Ultrametric Trees for Optimal Transport Regression AAAI 2024 Learning with Adaptive Resource Allocation ICML 2024 Learning with Fitzpatrick Losses NeurIPS 2024 Leveraging Continuous Time to Understand Momentum When Training Diagonal Linear Networks AISTATS 2024 Lexicographic Optimization: Algorithms and Stability AISTATS 2024 LibMOON: A Gradient-based MultiObjective OptimizatioN Library in PyTorch NeurIPS 2024 Light Unbalanced Optimal Transport NeurIPS 2024 Linear Time Approximation Algorithm for Column Subset Selection with Local Search NeurIPS 2024 Linear-time Differential Inverse Kinematics: an Augmented Lagrangian Perspective RSS 2024 Log Barriers for Safe Black-box Optimization with Application to Safe Reinforcement Learning JMLR 2024 Log-concave Sampling from a Convex Body with a Barrier: a Robust and Unified Dikin Walk NeurIPS 2024 Low Complexity Echo Delay Estimator Based on Binarized Feature Matching Interspeech 2024 Lower Complexity Adaptation for Empirical Entropic Optimal Transport JMLR 2024 Lower Complexity Bounds of Finite-Sum Optimization Problems: The Results and Construction JMLR 2024 Low-Latency Neural Stereo Streaming CVPR 2024 Low-Rank Bandits via Tight Two-to-Infinity Singular Subspace Recovery ICML 2024 Low-Rank Kernel Tensor Learning for Incomplete Multi-View Clustering AAAI 2024