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Theory

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Papers

Complexity of Inference in Latent Dirichlet Allocation NIPS 2011
A More Powerful Two-Sample Test in High Dimensions using Random Projection NIPS 2011
Uniqueness of Belief Propagation on Signed Graphs NIPS 2011
Learning in Hilbert vs. Banach Spaces: A Measure Embedding Viewpoint NIPS 2011
Finite Time Analysis of Stratified Sampling for Monte Carlo NIPS 2011
The Fast Convergence of Boosting NIPS 2011
Shallow vs. Deep Sum-Product Networks NIPS 2011
Expressive Power and Approximation Errors of Restricted Boltzmann Machines NIPS 2011
Selecting the State-Representation in Reinforcement Learning NIPS 2011
The Local Rademacher Complexity of Lp-Norm Multiple Kernel Learning NIPS 2011
Statistical Performance of Convex Tensor Decomposition NIPS 2011
Minimax Localization of Structural Information in Large Noisy Matrices NIPS 2011
Comparative Analysis of Viterbi Training and Maximum Likelihood Estimation for HMMs NIPS 2011
Noise Thresholds for Spectral Clustering NIPS 2011
A Convergence Analysis of Log-Linear Training NIPS 2011
Learning with the weighted trace-norm under arbitrary sampling distributions NIPS 2011
How biased are maximum entropy models? NIPS 2011
Discussion of “Learning Equivalence Classes of Acyclic Models with Latent and Selection Variables from Multiple Datasets with Overlapping Variables” AISTATS 2011
Discussion of “A conditional game for comparing approximations” AISTATS 2011
Improved Loss Bounds For Multiple Kernel Learning AISTATS 2011
Asymptotic Theory for Linear-Chain Conditional Random Fields AISTATS 2011
Error Analysis of Laplacian Eigenmaps for Semi-supervised Learning AISTATS 2011
Oracle inequalities for computationally budgeted model selection COLT 2011
Bandits, Query Learning, and the Haystack Dimension COLT 2011
Beyond the regret minimization barrier: an optimal algorithm for stochastic strongly-convex optimization COLT 2011