Theory

Theoretical Analysis of Bayesian Matrix Factorization JMLR 2011 Union Support Recovery in Multi-task Learning JMLR 2011 Uniqueness of Belief Propagation on Signed Graphs NeurIPS 2011 Analysis of Multi-stage Convex Relaxation for Sparse Regularization JMLR 2010 An analysis on negative curvature induced by singularity in multi-layer neural-network learning NeurIPS 2010 A Reduction from Apprenticeship Learning to Classification NeurIPS 2010 A Theory of Multiclass Boosting NeurIPS 2010 Basis Construction from Power Series Expansions of Value Functions NeurIPS 2010 Block Variable Selection in Multivariate Regression and High-dimensional Causal Inference NeurIPS 2010 Composite Binary Losses JMLR 2010 Convexity of Proper Composite Binary Losses AISTATS 2010 Empirical Bernstein Inequalities for U-Statistics NeurIPS 2010 Error Propagation for Approximate Policy and Value Iteration NeurIPS 2010 Exact inference and learning for cumulative distribution functions on loopy graphs NeurIPS 2010 Fractionally Predictive Spiking Neurons NeurIPS 2010 Identifying Cause and Effect on Discrete Data using Additive Noise Models AISTATS 2010 Improving the Asymptotic Performance of Markov Chain Monte-Carlo by Inserting Vortices NeurIPS 2010 Kernel Partial Least Squares is Universally Consistent AISTATS 2010 Learnability, Stability and Uniform Convergence JMLR 2010 Learning Exponential Families in High-Dimensions: Strong Convexity and Sparsity AISTATS 2010 Lifted Inference Seen from the Other Side : The Tractable Features NeurIPS 2010 Lower Bounds on Rate of Convergence of Cutting Plane Methods NeurIPS 2010 LSTD with Random Projections NeurIPS 2010 Near-optimal Regret Bounds for Reinforcement Learning JMLR 2010 Nonlinear functional regression: a functional RKHS approach AISTATS 2010