Optimization

Learning Maximum Margin Temporal Warping for Action Recognition ICCV 2013 Learning Multi-level Sparse Representations NeurIPS 2013 Learning Multiple Models via Regularized Weighting NeurIPS 2013 Learning Near-Optimal Cost-Sensitive Decision Policy for Object Detection ICCV 2013 Learning Optimally Sparse Support Vector Machines ICML 2013 Learning Policies for Contextual Submodular Prediction ICML 2013 Learning Social Infectivity in Sparse Low-rank Networks Using Multi-dimensional Hawkes Processes AISTATS 2013 Learning the beta-Divergence in Tweedie Compound Poisson Matrix Factorization Models ICML 2013 Learning to Estimate and Remove Non-uniform Image Blur CVPR 2013 Least Informative Dimensions NeurIPS 2013 Least Soft-Threshold Squares Tracking CVPR 2013 Linear Approximation to ADMM for MAP inference ACML 2013 Linear Convergence with Condition Number Independent Access of Full Gradients NeurIPS 2013 Linear Sequence Discriminant Analysis: A Model-Based Dimensionality Reduction Method for Vector Sequences ICCV 2013 Locally-Linear Learning Machines (L3M) ACML 2013 Low-Rank Matrix and Tensor Completion via Adaptive Sampling NeurIPS 2013 Lp-Norm IDF for Large Scale Image Search CVPR 2013 Machine Learning with Operational Costs JMLR 2013 Machine Teaching for Bayesian Learners in the Exponential Family NeurIPS 2013 Making a Science of Model Search: Hyperparameter Optimization in Hundreds of Dimensions for Vision Architectures ICML 2013 Marginals-to-Models Reducibility NeurIPS 2013 Margins, Shrinkage, and Boosting ICML 2013 Matrix Completion From any Given Set of Observations NeurIPS 2013 Matrix factorization with binary components NeurIPS 2013 Maximum Variance Correction with Application to A* Search ICML 2013