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07/03/2020
On Symbolically Encoding the Behavior of Random Forests
Recent work has shown that the input-output behavior of some machine lea...
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06/12/2020
A New Perspective on Learning Context-Specific Independence
Local structure such as context-specific independence (CSI) has received...
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04/05/2020
On Tractable Representations of Binary Neural Networks
We consider the compilation of a binary neural network's decision functi...
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12/21/2018
On the Relative Expressiveness of Bayesian and Neural Networks
A neural network computes a function. A central property of neural netwo...
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05/09/2018
A Symbolic Approach to Explaining Bayesian Network Classifiers
We propose an approach for explaining Bayesian network classifiers, whic...
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08/22/2017
On Relaxing Determinism in Arithmetic Circuits
The past decade has seen a significant interest in learning tractable pr...
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04/05/2015
Dual Decomposition from the Perspective of Relax, Compensate and then Recover
Relax, Compensate and then Recover (RCR) is a paradigm for approximate i...
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11/25/2014
Efficient Algorithms for Bayesian Network Parameter Learning from Incomplete Data
We propose an efficient family of algorithms to learn the parameters of ...
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10/16/2012
New Advances and Theoretical Insights into EDML
EDML is a recently proposed algorithm for learning MAP parameters in Bay...
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10/16/2012
Lifted Relax, Compensate and then Recover: From Approximate to Exact Lifted Probabilistic Inference
We propose an approach to lifted approximate inference for first-order p...
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07/04/2012
On Bayesian Network Approximation by Edge Deletion
We consider the problem of deleting edges from a Bayesian network for th...
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02/14/2012