165 citations · 488 across the 9 of their papers we have counts for
11 papers
A Biased Graph Neural Network Sampler with Near-Optimal Regret
Qingru Zhang, David Wipf, Quan Gan +1
Graph neural networks (GNN) have recently emerged as a vehicle for applying deep network architectures to graph and relational data. However, given the increasing size of industria…
Nonparametric Latent Tree Graphical Models: Inference, Estimation, and Structure Learning
Le Song, Han Liu, Ankur Parikh +1
Tree structured graphical models are powerful at expressing long range or hierarchical dependency among many variables, and have been widely applied in different areas of computer…
A Spectral Algorithm for Latent Junction Trees
Ankur P. Parikh, Le Song, Mariya Ishteva +2
Latent variable models are an elegant framework for capturing rich probabilistic dependencies in many applications. However, current approaches typically parametrize these models u…
Spectral Methods for Learning Multivariate Latent Tree Structure
Animashree Anandkumar, Kamalika Chaudhuri, Daniel Hsu +3
This work considers the problem of learning the structure of multivariate linear tree models, which include a variety of directed tree graphical models with continuous, discrete, a…
Kernel Belief Propagation
Le Song, Arthur Gretton, Danny Bickson +2
We propose a nonparametric generalization of belief propagation, Kernel Belief Propagation (KBP), for pairwise Markov random fields. Messages are represented as functions in a repr…
Infinite Hierarchical MMSB Model for Nested Communities/Groups in Social Networks
Qirong Ho, Ankur P. Parikh, Le Song +1
Actors in realistic social networks play not one but a number of diverse roles depending on whom they interact with, and a large number of such role-specific interactions collectiv…