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Statistical Learning

4076 directly classified papers

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Papers

Markov Network Estimation From Multi-attribute Data ICML 2013
Guaranteed Sparse Recovery under Linear Transformation ICML 2013
Differentially Private Learning with Kernels ICML 2013
Thompson Sampling for Contextual Bandits with Linear Payoffs ICML 2013
Estimating Unknown Sparsity in Compressed Sensing ICML 2013
Two-Sided Exponential Concentration Bounds for Bayes Error Rate and Shannon Entropy ICML 2013
A Kernel Test for Three-Variable Interactions NIPS 2013
Permutation estimation and minimax rates of identifiability AISTATS 2013
Regularized Spectral Clustering under the Degree-Corrected Stochastic Blockmodel NIPS 2013
BIG & QUIC: Sparse Inverse Covariance Estimation for a Million Variables NIPS 2013
Stability of Multi-Task Kernel Regression Algorithms ACML 2013
Random Projections as Regularizers: Learning a Linear Discriminant Ensemble from Fewer Observations than Dimensions ACML 2013
Minimax Theory for High-dimensional Gaussian Mixtures with Sparse Mean Separation NIPS 2013
Large Scale Distributed Sparse Precision Estimation NIPS 2013
Local Privacy and Minimax Bounds: Sharp Rates for Probability Estimation NIPS 2013
A Comparative Framework for Preconditioned Lasso Algorithms NIPS 2013
Statistical Active Learning Algorithms NIPS 2013
Sensor Selection in High-Dimensional Gaussian Trees with Nuisances NIPS 2013
Dirty Statistical Models NIPS 2013
A Unified Robust Regression Model for Lasso-like Algorithms ICML 2013
On the Statistical Consistency of Algorithms for Binary Classification under Class Imbalance ICML 2013
Spectral Learning of Hidden Markov Models from Dynamic and Static Data ICML 2013
Modeling Information Propagation with Survival Theory ICML 2013
Sharp Generalization Error Bounds for Randomly-projected Classifiers ICML 2013
Computation-Risk Tradeoffs for Covariance-Thresholded Regression ICML 2013