Mathematics & Optimization

Learning Social Infectivity in Sparse Low-rank Networks Using Multi-dimensional Hawkes Processes AISTATS 2013 Learning Structured Low-Rank Representations for Image Classification CVPR 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 Learning Triggering Kernels for Multi-dimensional Hawkes Processes ICML 2013 Learning with Invariance via Linear Functionals on Reproducing Kernel Hilbert Space NeurIPS 2013 Least Informative Dimensions NeurIPS 2013 Lifting 3D Manhattan Lines from a Single Image ICCV 2013 Linear Convergence with Condition Number Independent Access of Full Gradients NeurIPS 2013 Linear decision rule as aspiration for simple decision heuristics NeurIPS 2013 Linearized Alternating Direction Method with Parallel Splitting and Adaptive Penalty for Separable Convex Programs in Machine Learning ACML 2013 Local Deep Kernel Learning for Efficient Non-linear SVM Prediction ICML 2013 Localization and Adaptation in Online Learning AISTATS 2013 Local Low-Rank Matrix Approximation ICML 2013 Locally Adaptive Bayesian Multivariate Time Series NeurIPS 2013 Local Privacy and Minimax Bounds: Sharp Rates for Probability Estimation NeurIPS 2013 Log-Euclidean Kernels for Sparse Representation and Dictionary Learning ICCV 2013 Loss-Proportional Subsampling for Subsequent ERM ICML 2013 Lovasz theta function, SVMs and Finding Dense Subgraphs JMLR 2013 Lower Bounds and Selectivity of Weak-Consistent Policies in Stochastic Multi-Armed Bandit Problem JMLR 2013 Low-Rank Matrix and Tensor Completion via Adaptive Sampling NeurIPS 2013 Machine Teaching for Bayesian Learners in the Exponential Family NeurIPS 2013 Marginals-to-Models Reducibility NeurIPS 2013 Markov Network Estimation From Multi-attribute Data ICML 2013 Matrix Completion From any Given Set of Observations NeurIPS 2013