Theory

On the Convergence Properties of Contrastive Divergence AISTATS 2010 On the relation between universality, characteristic kernels and RKHS embedding of measures AISTATS 2010 Pairwise Measures of Causal Direction in Linear Non-Gaussian Acyclic Models ACML 2010 Permutation Complexity Bound on Out-Sample Error NeurIPS 2010 Polynomial-Time Exact Inference in NP-Hard Binary MRFs via Reweighted Perfect Matching AISTATS 2010 Posterior distributions are computable from predictive distributions AISTATS 2010 Random Projection Trees Revisited NeurIPS 2010 Risk Bounds for Levy Processes in the PAC-Learning Framework AISTATS 2010 Spectral Regularization for Support Estimation NeurIPS 2010 Stability Approach to Regularization Selection (StARS) for High Dimensional Graphical Models NeurIPS 2010 The LASSO risk: asymptotic results and real world examples NeurIPS 2010 The Smooth Curvature Flexure Model: An Accurate, Low-Dimensional Approach for Robot Analysis RSS 2010 Towards Property-Based Classification of Clustering Paradigms NeurIPS 2010 Two-Layer Generalization Analysis for Ranking Using Rademacher Average NeurIPS 2010 Universal Kernels on Non-Standard Input Spaces NeurIPS 2010 Why Does Unsupervised Pre-training Help Deep Learning? JMLR 2010 Worst-case bounds on the quality of max-product fixed-points NeurIPS 2010 Adaptive False Discovery Rate Control under Independence and Dependence JMLR 2009 A Fast, Consistent Kernel Two-Sample Test NeurIPS 2009 Asymptotically Optimal Regularization in Smooth Parametric Models NeurIPS 2009 Asymptotic Analysis of MAP Estimation via the Replica Method and Compressed Sensing NeurIPS 2009 A unified framework for high-dimensional analysis of M-estimators with decomposable regularizers NeurIPS 2009 Complexity of Decentralized Control: Special Cases NeurIPS 2009 Deterministic Error Analysis of Support Vector Regression and Related Regularized Kernel Methods JMLR 2009 Discrete MDL Predicts in Total Variation NeurIPS 2009