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Showing 1 to 3 of 3 for “"Knowledge Compilation"”.
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On Training Neurons with Bounded Compilations
<p>Knowledge compilation offers a formal approach to explaining and verifying the behavior of machine learning systems, such as neural networks. Unfortunately, compiling even an individual neuron into a tractable representation such as an Ordered Binary Decision Diagram (OBDD), is an NP-hard …
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Scalable Structure Learning, Inference, and Analysis with Probabilistic Programs
… programming language that integrates knowledge compilation and symbolic analysis to compute sound exact answers to many Bayesian inference queries about both hand-written and machine-synthesized probabilistic programs. Third, I present fast algorithms for analyzing statistical …
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Partial compilation of constraint problems
… etc. Most such queries are NP-hard problems. Knowledge Compilation (KC) methods were developed to deal with the complexity of solving combinatorial problems online by creating a representation offline that is able to answer queries in time that is polynomial in the size of the representation …