Optimization

Learning-Augmented Dynamic Submodular Maximization NeurIPS 2024 Learning-based rigid tube model predictive control L4DC 2024 Learning Bregman Divergences with Application to Robustness NeurIPS 2024 Learning Cut Generating Functions for Integer Programming NeurIPS 2024 Learning diffusion at lightspeed NeurIPS 2024 Learning Diffusions under Uncertainty AAAI 2024 Learning Distributions on Manifolds with Free-Form Flows NeurIPS 2024 Learning-Efficient Yet Generalizable Collaborative Filtering for Item Recommendation ICML 2024 Learning Energy Decompositions for Partial Inference in GFlowNets ICLR 2024 Learning Equilibria in Adversarial Team Markov Games: A Nonconvex-Hidden-Concave Min-Max Optimization Problem NeurIPS 2024 Learning Exceptional Subgroups by End-to-End Maximizing KL-Divergence ICML 2024 Learning Fair Policies for Multi-Stage Selection Problems from Observational Data AAAI 2024 Learning flow functions of spiking systems L4DC 2024 Learning for CasADi: Data-driven Models in Numerical Optimization L4DC 2024 Learning for Transductive Threshold Calibration in Open-World Recognition CVPR 2024 Learning from Aggregate responses: Instance Level versus Bag Level Loss Functions ICLR 2024 Learning from Noisy Labels via Conditional Distributionally Robust Optimization NeurIPS 2024 Learning from Streaming Data when Users Choose ICML 2024 Learning Generalized Linear Programming Value Functions NeurIPS 2024 Learning General Parameterized Policies for Infinite Horizon Average Reward Constrained MDPs via Primal-Dual Policy Gradient Algorithm NeurIPS 2024 Learning in CubeRes Model Space for Anomaly Detection in 3D GPR Data IJCAI 2024 Learning model uncertainty as variance-minimizing instance weights ICLR 2024 Learning Multi-Task Sparse Representation Based on Fisher Information AAAI 2024 Learning Neural Contracting Dynamics: Extended Linearization and Global Guarantees NeurIPS 2024 Learning Optimal Dynamic Treatment Regimens Subject to Stagewise Risk Controls JMLR 2024