Probability

PC Algorithm for Nonparanormal Graphical Models JMLR 2013 Projecting Ising Model Parameters for Fast Mixing NeurIPS 2013 Recursive Karcher Expectation Estimators And Geometric Law of Large Numbers AISTATS 2013 Robust Low Rank Kernel Embeddings of Multivariate Distributions NeurIPS 2013 Saliency Detection via Absorbing Markov Chain ICCV 2013 Scene Parsing by Integrating Function, Geometry and Appearance Models CVPR 2013 Sensor Selection in High-Dimensional Gaussian Trees with Nuisances NeurIPS 2013 Sign Cauchy Projections and Chi-Square Kernel NeurIPS 2013 Sinkhorn Distances: Lightspeed Computation of Optimal Transport NeurIPS 2013 Solving inverse problem of Markov chain with partial observations NeurIPS 2013 Sparse Gaussian Conditional Random Fields: Algorithms, Theory, and Application to Energy Forecasting ICML 2013 Sparse/Robust Estimation and Kalman Smoothing with Nonsmooth Log-Concave Densities: Modeling, Computation, and Theory JMLR 2013 Spectral Learning of Hidden Markov Models from Dynamic and Static Data ICML 2013 Stability of Multi-Task Kernel Regression Algorithms ACML 2013 Taming the Curse of Dimensionality: Discrete Integration by Hashing and Optimization ICML 2013 The Randomized Dependence Coefficient NeurIPS 2013 Two-Sided Exponential Concentration Bounds for Bayes Error Rate and Shannon Entropy ICML 2013 Using Hyperbolic Cross Approximation to measure and compensate Covariate Shift ACML 2013 What do row and column marginals reveal about your dataset? NeurIPS 2013 A Characterization of Scoring Rules for Linear Properties COLT 2012 Adaptive Stratified Sampling for Monte-Carlo integration of Differentiable functions NeurIPS 2012 Ancestor Sampling for Particle Gibbs NeurIPS 2012 A Note on Metric Properties for Some Divergence Measures: The Gaussian Case ACML 2012 Approximating Concavely Parameterized Optimization Problems NeurIPS 2012 Bayesian estimation of discrete entropy with mixtures of stick-breaking priors NeurIPS 2012