Mathematics & Optimization

Large Scale computation of Means and Clusters for Persistence Diagrams using Optimal Transport NeurIPS 2018 Large-Scale Cox Process Inference using Variational Fourier Features ICML 2018 Large Scale Empirical Risk Minimization via Truncated Adaptive Newton Method AISTATS 2018 Large-Scale Sparse Inverse Covariance Estimation via Thresholding and Max-Det Matrix Completion ICML 2018 Large-Scale Stochastic Sampling from the Probability Simplex NeurIPS 2018 Latent RANSAC CVPR 2018 Layerwise Systematic Scan: Deep Boltzmann Machines and Beyond AISTATS 2018 Leadership in Singleton Congestion Games IJCAI 2018 LeapsAndBounds: A Method for Approximately Optimal Algorithm Configuration ICML 2018 Learners that Use Little Information ALT 2018 Learning a Mixture of Two Multinomial Logits ICML 2018 Learning Bounds for Greedy Approximation with Explicit Feature Maps from Multiple Kernels NeurIPS 2018 Learning Certifiably Optimal Rule Lists for Categorical Data JMLR 2018 Learning convex bounds for linear quadratic control policy synthesis NeurIPS 2018 Learning convex polytopes with margin NeurIPS 2018 Learning Descriptor Networks for 3D Shape Synthesis and Analysis CVPR 2018 Learning Diffusion using Hyperparameters ICML 2018 Learning filter widths of spectral decompositions with wavelets NeurIPS 2018 Learning from Comparisons and Choices JMLR 2018 Learning from Group Comparisons: Exploiting Higher Order Interactions NeurIPS 2018 Learning Generative ConvNets via Multi-Grid Modeling and Sampling CVPR 2018 Learning Generative Models with Sinkhorn Divergences AISTATS 2018 Learning in Reproducing Kernel Kreı̆n Spaces ICML 2018 Learning Latent Permutations with Gumbel-Sinkhorn Networks ICLR 2018 Learning Localized Spatio-Temporal Models From Streaming Data ICML 2018