Statistical Learning

Relational Learning with One Network: An Asymptotic Analysis AISTATS 2011 Relative Density-Ratio Estimation for Robust Distribution Comparison NeurIPS 2011 Safe Learning: bridging the gap between Bayes, MDL and statistical learning theory via empirical convexity COLT 2011 Scalable Training of Mixture Models via Coresets NeurIPS 2011 Selecting the State-Representation in Reinforcement Learning NeurIPS 2011 Sequential Event Prediction with Association Rules COLT 2011 Sparse Estimation with Structured Dictionaries NeurIPS 2011 Sparsity Regret Bounds for Individual Sequences in Online Linear Regression COLT 2011 Spectral Dimensionality Reduction via Maximum Entropy AISTATS 2011 Statistical Performance of Convex Tensor Decomposition NeurIPS 2011 Statistical Tests for Optimization Efficiency NeurIPS 2011 Structural equations and divisive normalization for energy-dependent component analysis NeurIPS 2011 Testing a Bayesian Measure of Representativeness Using a Large Image Database NeurIPS 2011 The Impact of Unlabeled Patterns in Rademacher Complexity Theory for Kernel Classifiers NeurIPS 2011 The Local Rademacher Complexity of Lp-Norm Multiple Kernel Learning NeurIPS 2011 The Neural Autoregressive Distribution Estimator AISTATS 2011 The Sample Complexity of Dictionary Learning COLT 2011 Tight conditions for consistent variable selection in high dimensional nonparametric regression COLT 2011 Unifying Framework for Fast Learning Rate of Non-Sparse Multiple Kernel Learning NeurIPS 2011 Unifying Non-Maximum Likelihood Learning Objectives with Minimum KL Contraction NeurIPS 2011 Universal low-rank matrix recovery from Pauli measurements NeurIPS 2011 A Constant-Time Algorithm for Vector Field SLAM using an Exactly Sparse Extended Information Filter RSS 2010 Active Estimation of F-Measures NeurIPS 2010 A New Probabilistic Model for Rank Aggregation NeurIPS 2010 An Investigation of Missing Data Methods for Classification Trees Applied to Binary Response Data JMLR 2010