Optimization

LAG: Lazily Aggregated Gradient for Communication-Efficient Distributed Learning NeurIPS 2018 Large Scale computation of Means and Clusters for Persistence Diagrams using Optimal Transport NeurIPS 2018 Large Scale Empirical Risk Minimization via Truncated Adaptive Newton Method AISTATS 2018 Large Scale Optimal Transport and Mapping Estimation ICLR 2018 LDMNet: Low Dimensional Manifold Regularized Neural Networks CVPR 2018 LeapsAndBounds: A Method for Approximately Optimal Algorithm Configuration ICML 2018 Learning Beam Search Policies via Imitation Learning NeurIPS 2018 Learning Compact Neural Networks with Regularization ICML 2018 Learning Compact Recurrent Neural Networks With Block-Term Tensor Decomposition CVPR 2018 “Learning-Compression” Algorithms for Neural Net Pruning CVPR 2018 Learning convex bounds for linear quadratic control policy synthesis NeurIPS 2018 Learning Generative Models with Sinkhorn Divergences AISTATS 2018 Learning Implicit Generative Models with the Method of Learned Moments ICML 2018 Learning in Reproducing Kernel Kreı̆n Spaces ICML 2018 Learning Intrinsic Sparse Structures within Long Short-Term Memory ICLR 2018 Learning latent variable structured prediction models with Gaussian perturbations NeurIPS 2018 Learning Multi-Instance Enriched Image Representations via Non-Greedy Ratio Maximization of the l1-Norm Distances CVPR 2018 Learning One-hidden-layer Neural Networks with Landscape Design ICLR 2018 Learning Parametric Closed-Loop Policies for Markov Potential Games ICLR 2018 Learning Spatial-Temporal Regularized Correlation Filters for Visual Tracking CVPR 2018 Learning Steerable Filters for Rotation Equivariant CNNs CVPR 2018 Learning Time/Memory-Efficient Deep Architectures With Budgeted Super Networks CVPR 2018 Learning to Exploit Invariances in Clinical Time-Series Data using Sequence Transformer Networks MLHC 2018 Learning to Optimize Combinatorial Functions ICML 2018 Learning to Round for Discrete Labeling Problems AISTATS 2018