sample complexity

Memory Limited, Streaming PCA NeurIPS 2013 Minimax Theory for High-dimensional Gaussian Mixtures with Sparse Mean Separation NeurIPS 2013 More data speeds up training time in learning halfspaces over sparse vectors NeurIPS 2013 On the Sample Complexity of Subspace Learning NeurIPS 2013 Passive Learning with Target Risk COLT 2013 Phase Retrieval using Alternating Minimization NeurIPS 2013 The Sample-Complexity of General Reinforcement Learning ICML 2013 Using multiple samples to learn mixture models NeurIPS 2013 Active Learning of Multi-Index Function Models NeurIPS 2012 Competitive Classification and Closeness Testing COLT 2012 Dimensionality Dependent PAC-Bayes Margin Bound NeurIPS 2012 Learning Fourier Sparse Set Functions AISTATS 2012 Learning from Weak Teachers AISTATS 2012 Learning Mixtures of Tree Graphical Models NeurIPS 2012 Multi-Instance Learning with Any Hypothesis Class JMLR 2012 Near-optimal Differentially Private Principal Components NeurIPS 2012 Non-parametric Approximate Dynamic Programming via the Kernel Method NeurIPS 2012 On the Sample Complexity of Robust PCA NeurIPS 2012 Provable ICA with Unknown Gaussian Noise, with Implications for Gaussian Mixtures and Autoencoders NeurIPS 2012 There’s a Hole in My Data Space: Piecewise Predictors for Heterogeneous Learning Problems AISTATS 2012 Using More Data to Speed-up Training Time AISTATS 2012 Error Analysis of Laplacian Eigenmaps for Semi-supervised Learning AISTATS 2011 Lower Bounds for Passive and Active Learning NeurIPS 2011 Missing Information Impediments to Learnability COLT 2011 Models of Cooperative Teaching and Learning JMLR 2011