Statistical Learning

GEV-Canonical Regression for Accurate Binary Class Probability Estimation when One Class is Rare ICML 2014 Heavy-tailed regression with a generalized median-of-means ICML 2014 High-Dimensional Covariance Decomposition into Sparse Markov and Independence Models JMLR 2014 Kernel Mean Estimation via Spectral Filtering NeurIPS 2014 Latent Variable Copula Inference for Bundle Pricing from Retail Transaction Data ICML 2014 Learnability of the Superset Label Learning Problem ICML 2014 Learning convolution filters for inverse covariance estimation of neural network connectivity NeurIPS 2014 Learning Graphs with a Few Hubs ICML 2014 Learning Mixtures of Linear Classifiers ICML 2014 Learning on graphs using Orthonormal Representation is Statistically Consistent NeurIPS 2014 Learning Shuffle Ideals Under Restricted Distributions NeurIPS 2014 Learning Time-Varying Coverage Functions NeurIPS 2014 Learning with Fredholm Kernels NeurIPS 2014 Learning without concentration COLT 2014 Localized Complexities for Transductive Learning COLT 2014 Low-dimensional models of neural population activity in sensory cortical circuits NeurIPS 2014 Lower Bounds on the Performance of Polynomial-time Algorithms for Sparse Linear Regression COLT 2014 Maximum Mean Discrepancy for Class Ratio Estimation: Convergence Bounds and Kernel Selection ICML 2014 Methods of Moments for Learning Stochastic Languages: Unified Presentation and Empirical Comparison ICML 2014 Minimax-optimal Inference from Partial Rankings NeurIPS 2014 Multiple Testing under Dependence via Semiparametric Graphical Models ICML 2014 Multivariate f-divergence Estimation With Confidence NeurIPS 2014 Multivariate General Linear Models (MGLM) on Riemannian Manifolds with Applications to Statistical Analysis of Diffusion Weighted Images CVPR 2014 Multivariate Maximal Correlation Analysis ICML 2014 (Near) Dimension Independent Risk Bounds for Differentially Private Learning ICML 2014