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02/01/2023
Deep Dependency Networks for Multi-Label Classification
We propose a simple approach which combines the strengths of probabilist...
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05/05/2020
Don't Explain without Verifying Veracity: An Evaluation of Explainable AI with Video Activity Recognition
Explainable machine learning and artificial intelligence models have bee...
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07/03/2018
Domain Aware Markov Logic Networks
Combining logic and probability has been a long standing goal of AI. Mar...
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07/02/2018
Lifted Marginal MAP Inference
Lifted inference reduces the complexity of inference in relational proba...
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06/14/2018
Scalable Neural Network Compression and Pruning Using Hard Clustering and L1 Regularization
We propose a simple and easy to implement neural network compression alg...
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06/30/2016
Lifted Region-Based Belief Propagation
Due to the intractable nature of exact lifted inference, research has re...
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01/15/2014
Join-Graph Propagation Algorithms
The paper investigates parameterized approximate message-passing schemes...
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09/26/2013
Structured Message Passing
In this paper, we present structured message passing (SMP), a unifying f...
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07/11/2012
A Complete Anytime Algorithm for Treewidth
In this paper, we present a Branch and Bound algorithm called QuickBB fo...
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07/04/2012
Approximate Inference Algorithms for Hybrid Bayesian Networks with Discrete Constraints
In this paper, we consider Hybrid Mixed Networks (HMN) which are Hybrid ...
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07/04/2012
Modeling Transportation Routines using Hybrid Dynamic Mixed Networks
This paper describes a general framework called Hybrid Dynamic Mixed Net...
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06/13/2012
AND/OR Importance Sampling
The paper introduces AND/OR importance sampling for probabilistic graphi...
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03/15/2012
Formula-Based Probabilistic Inference
Computing the probability of a formula given the probabilities or weight...
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02/14/2012
Probabilistic Theorem Proving
Many representation schemes combining first-order logic and probability ...
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02/14/2012
