Statistical Learning

Sparse PCA via Covariance Thresholding NeurIPS 2014 Sparse PCA with Oracle Property NeurIPS 2014 Sparsity and the Truncated l^2-norm AISTATS 2014 Spectral Learning of Latent-Variable PCFGs: Algorithms and Sample Complexity JMLR 2014 Spectral Methods for Supervised Topic Models NeurIPS 2014 Statistical analysis of stochastic gradient methods for generalized linear models ICML 2014 Statistical-Computational Phase Transitions in Planted Models: The High-Dimensional Setting ICML 2014 Stereo under Sequential Optimal Sampling: A Statistical Analysis Framework for Search Space Reduction CVPR 2014 Structure learning of antiferromagnetic Ising models NeurIPS 2014 Tensor Decompositions for Learning Latent Variable Models JMLR 2014 The Falling Factorial Basis and Its Statistical Applications ICML 2014 The More, the Merrier: the Blessing of Dimensionality for Learning Large Gaussian Mixtures COLT 2014 The Noisy Power Method: A Meta Algorithm with Applications NeurIPS 2014 The sample complexity of agnostic learning under deterministic labels COLT 2014 Tight Bounds for Influence in Diffusion Networks and Application to Bond Percolation and Epidemiology NeurIPS 2014 Tight Bounds for the Expected Risk of Linear Classifiers and PAC-Bayes Finite-Sample Guarantees AISTATS 2014 Tighten after Relax: Minimax-Optimal Sparse PCA in Polynomial Time NeurIPS 2014 Time--Data Tradeoffs by Aggressive Smoothing NeurIPS 2014 Understanding the Limiting Factors of Topic Modeling via Posterior Contraction Analysis ICML 2014 Achievability of Asymptotic Minimax Regret in Online and Batch Prediction ACML 2013 A Comparative Framework for Preconditioned Lasso Algorithms NeurIPS 2013 A Competitive Test for Uniformity of Monotone Distributions AISTATS 2013 Activized Learning with Uniform Classification Noise ICML 2013 Adaptivity to Local Smoothness and Dimension in Kernel Regression NeurIPS 2013 A Kernel Test for Three-Variable Interactions NeurIPS 2013