Mathematics & Optimization

Learning a Latent Simplex in Input Sparsity Time ICLR 2021 Learning a mixture of two subspaces over finite fields ALT 2021 Learning and Testing Irreducible Markov Chains via the k-Cover Time ALT 2021 Learning Approximate Forward Reachable Sets Using Separating Kernels L4DC 2021 Learning-Augmented Dynamic Power Management with Multiple States via New Ski Rental Bounds NeurIPS 2021 Learning Augmented Methods for Matching: Improving Invasive Species Management and Urban Mobility AAAI 2021 Learning Branching Heuristics for Propositional Model Counting AAAI 2021 Learning by Watching CVPR 2021 Learning Complexity of Simulated Annealing AISTATS 2021 Learning Deep Generative Models for Queuing Systems AAAI 2021 Learning Deep Latent Variable Models by Short-Run MCMC Inference With Optimal Transport Correction CVPR 2021 Learning Dynamics Models with Stable Invariant Sets AAAI 2021 Learning Equilibria in Matching Markets from Bandit Feedback NeurIPS 2021 Learning from History for Byzantine Robust Optimization ICML 2021 Learning Gaussian Mixtures with Generalized Linear Models: Precise Asymptotics in High-dimensions NeurIPS 2021 Learning Graph Models for Retrosynthesis Prediction NeurIPS 2021 Learning Graphons via Structured Gromov-Wasserstein Barycenters AAAI 2021 Learning in Markets: Greed Leads to Chaos but Following the Price is Right IJCAI 2021 Learning in Matrix Games can be Arbitrarily Complex COLT 2021 Learning in Multi-Stage Decentralized Matching Markets NeurIPS 2021 Learning in Non-Cooperative Configurable Markov Decision Processes NeurIPS 2021 Learning Interaction Kernels for Agent Systems on Riemannian Manifolds ICML 2021 Learning interaction kernels in heterogeneous systems of agents from multiple trajectories JMLR 2021 Learning Interpretable Decision Rule Sets: A Submodular Optimization Approach NeurIPS 2021 Learning Laplacian Matrix from Graph Signals with Sparse Spectral Representation JMLR 2021