Statistics

Sparse Principal Component Analysis for High Dimensional Multivariate Time Series AISTATS 2013 Spectral methods for neural characterization using generalized quadratic models NeurIPS 2013 Speeding up Permutation Testing in Neuroimaging NeurIPS 2013 Structure Learning of Mixed Graphical Models AISTATS 2013 The Randomized Dependence Coefficient NeurIPS 2013 Variable Selection in High-Dimension with Random Designs and Orthogonal Matching Pursuit JMLR 2013 Active Learning of Multi-Index Function Models NeurIPS 2012 A Kernel Two-Sample Test JMLR 2012 A Note on Metric Properties for Some Divergence Measures: The Gaussian Case ACML 2012 Assessing Blinding in Clinical Trials NeurIPS 2012 Bayesian Comparison of Machine Learning Algorithms on Single and Multiple Datasets AISTATS 2012 Coding efficiency and detectability of rate fluctuations with non-Poisson neuronal firing NeurIPS 2012 Consistent Model Selection Criteria on High Dimensions JMLR 2012 Dimensionality Dependent PAC-Bayes Margin Bound NeurIPS 2012 Ensemble weighted kernel estimators for multivariate entropy estimation NeurIPS 2012 Fast Resampling Weighted v-Statistics NeurIPS 2012 High-dimensional Sparse Inverse Covariance Estimation using Greedy Methods AISTATS 2012 L1 Covering Numbers for Uniformly Bounded Convex Functions COLT 2012 Learning High-Density Regions for a Generalized Kolmogorov-Smirnov Test in High-Dimensional Data NeurIPS 2012 Link Prediction in Graphs with Autoregressive Features NeurIPS 2012 MCMC for continuous-time discrete-state systems NeurIPS 2012 Meta-Gaussian Information Bottleneck NeurIPS 2012 Multi-Task Averaging NeurIPS 2012 Near-optimal Differentially Private Principal Components NeurIPS 2012 On Sparse, Spectral and Other Parameterizations of Binary Probabilistic Models AISTATS 2012