Mathematics & Optimization

Learning latent causal graphs via mixture oracles NeurIPS 2021 Learning local modules in dynamic networks L4DC 2021 Learning Models as Functionals of Signed-Distance Fields for Manipulation Planning CoRL 2021 Learning Multi-Scale Photo Exposure Correction CVPR 2021 Learning of Structurally Unambiguous Probabilistic Grammars AAAI 2021 Learning Online Algorithms with Distributional Advice ICML 2021 Learning on Random Balls is Sufficient for Estimating (Some) Graph Parameters NeurIPS 2021 Learning Optimal Auctions with Correlated Valuations from Samples ICML 2021 Learning partial correlation graphs and graphical models by covariance queries JMLR 2021 Learning Partially Observed Linear Dynamical Systems from Logarithmic Number of Samples L4DC 2021 Learning Riemannian Manifolds for Geodesic Motion Skills RSS 2021 Learning Set Functions that are Sparse in Non-Orthogonal Fourier Bases AAAI 2021 Learning Shared Subgraphs in Ising Model Pairs AISTATS 2021 Learning Sparse Classifiers: Continuous and Mixed Integer Optimization Perspectives JMLR 2021 Learning Stabilizing Controllers for Unstable Linear Quadratic Regulators from a Single Trajectory L4DC 2021 Learning Stochastic Behaviour from Aggregate Data ICML 2021 Learning Strategies in Decentralized Matching Markets under Uncertain Preferences JMLR 2021 Learning Tensor Low-Rank Prior for Hyperspectral Image Reconstruction CVPR 2021 Learning the Dynamics of Time Delay Systems with Trainable Delays L4DC 2021 Learning the optimal Tikhonov regularizer for inverse problems NeurIPS 2021 Learning the Pareto Front with Hypernetworks ICLR 2021 Learning to delegate for large-scale vehicle routing NeurIPS 2021 Learning to Learn Graph Topologies NeurIPS 2021 Learning-to-learn non-convex piecewise-Lipschitz functions NeurIPS 2021 Learning to Make Decisions via Submodular Regularization ICLR 2021