Mathematics & Optimization

Learning Neural Constitutive Laws from Motion Observations for Generalizable PDE Dynamics ICML 2023 Learning Nonlinear Causal Effect via Kernel Anchor Regression UAI 2023 Learning Partial Differential Equations in Reproducing Kernel Hilbert Spaces JMLR 2023 Learning Preconditioners for Conjugate Gradient PDE Solvers ICML 2023 Learning Preference Models with Sparse Interactions of Criteria IJCAI 2023 Learning-Rate-Free Learning by D-Adaptation ICML 2023 Learning Rate Free Sampling in Constrained Domains NeurIPS 2023 Learning Regions of Interest for Bayesian Optimization with Adaptive Level-Set Estimation ICML 2023 Learning Regularized Monotone Graphon Mean-Field Games NeurIPS 2023 Learning Relational Causal Models with Cycles through Relational Acyclification AAAI 2023 Learning Revenue Maximization Using Posted Prices for Stochastic Strategic Patient Buyers AAAI 2023 Learning Sparse Graphon Mean Field Games AISTATS 2023 Learning Sparse Group Models Through Boolean Relaxation ICLR 2023 Learning the Efficient Frontier NeurIPS 2023 Learning the Right Layers a Data-Driven Layer-Aggregation Strategy for Semi-Supervised Learning on Multilayer Graphs ICML 2023 Learning to Bid in Repeated First-Price Auctions with Budgets ICML 2023 Learning to Break Symmetries for Efficient Optimization in Answer Set Programming AAAI 2023 Learning to Configure Separators in Branch-and-Cut NeurIPS 2023 Learning to Count Isomorphisms with Graph Neural Networks AAAI 2023 Learning To Dive In Branch And Bound NeurIPS 2023 Learning to Generate Columns with Application to Vertex Coloring ICLR 2023 Learning to Optimize with Stochastic Dominance Constraints AISTATS 2023 Learning to Rank under Multinomial Logit Choice JMLR 2023 Learning to Search Feasible and Infeasible Regions of Routing Problems with Flexible Neural k-Opt NeurIPS 2023 Learning When to Use Automatic Tabulation in Constraint Model Reformulation IJCAI 2023