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Poster
Wed 9:00 Achieving the KS threshold in the general stochastic block model with linearized acyclic belief propagation
Emmanuel Abbe · Colin Sandon
Poster
Tue 9:00 Identification and Overidentification of Linear Structural Equation Models
Bryant Chen
Poster
Mon 9:00 Graph Clustering: Block-models and model free results
Yali Wan · Marina Meila
Poster
Tue 9:00 Constraints Based Convex Belief Propagation
Yaniv Tenzer · Alex Schwing · Kevin Gimpel · Tamir Hazan
Poster
Tue 9:00 Probabilistic Inference with Generating Functions for Poisson Latent Variable Models
Kevin Winner · Daniel Sheldon
Poster
Mon 9:00 Reconstructing Parameters of Spreading Models from Partial Observations
Andrey Lokhov
Poster
Mon 9:00 Neurally-Guided Procedural Models: Amortized Inference for Procedural Graphics Programs using Neural Networks
Daniel Ritchie · Anna Thomas · Pat Hanrahan · Noah Goodman
Poster
Wed 9:00 Solving Marginal MAP Problems with NP Oracles and Parity Constraints
Yexiang Xue · zhiyuan li · Stefano Ermon · Carla Gomes · Bart Selman
Workshop
Sat 0:30 Mladen Kolar. Post-Regularization Inference for Dynamic Nonparanormal Graphical Models.
Mladen Kolar
Poster
Tue 9:00 Variational Information Maximization for Feature Selection
Shuyang Gao · Greg Ver Steeg · Aram Galstyan
Poster
Wed 9:00 A Unified Approach for Learning the Parameters of Sum-Product Networks
Han Zhao · Pascal Poupart · Geoffrey Gordon
Poster
Wed 9:00 A Probabilistic Framework for Deep Learning
Ankit Patel · Tan Nguyen · Richard Baraniuk