Mathematics

Exact inference and learning for cumulative distribution functions on loopy graphs NeurIPS 2010 Exact learning curves for Gaussian process regression on large random graphs NeurIPS 2010 Extensions of Generalized Binary Search to Group Identification and Exponential Costs NeurIPS 2010 Fractionally Predictive Spiking Neurons NeurIPS 2010 Generalized roof duality and bisubmodular functions NeurIPS 2010 Getting lost in space: Large sample analysis of the resistance distance NeurIPS 2010 Graph Kernels JMLR 2010 Graph-Valued Regression NeurIPS 2010 Guaranteed Rank Minimization via Singular Value Projection NeurIPS 2010 Hilbert Space Embeddings and Metrics on Probability Measures JMLR 2010 Identifying Dendritic Processing NeurIPS 2010 Identifying graph-structured activation patterns in networks NeurIPS 2010 Inference of Sparse Networks with Unobserved Variables. Application to Gene Regulatory Networks AISTATS 2010 Inference with Multivariate Heavy-Tails in Linear Models NeurIPS 2010 Kronecker Graphs: An Approach to Modeling Networks JMLR 2010 Learning Gradients: Predictive Models that Infer Geometry and Statistical Dependence JMLR 2010 Learning Networks of Stochastic Differential Equations NeurIPS 2010 Learning sparse dynamic linear systems using stable spline kernels and exponential hyperpriors NeurIPS 2010 Link Discovery using Graph Feature Tracking NeurIPS 2010 Maximum-likelihood learning of cumulative distribution functions on graphs AISTATS 2010 Message-passing for Graph-structured Linear Programs: Proximal Methods and Rounding Schemes JMLR 2010 Model Selection: Beyond the Bayesian/Frequentist Divide JMLR 2010 Multitask Learning without Label Correspondences NeurIPS 2010 -Nested Symmetric Distributions JMLR 2010 Nonparametric Tree Graphical Models AISTATS 2010