Gabi Teodoru

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Latent variable models are an elegant framework for capturing rich probabilistic dependencies in many applications. However, current approaches typically parametrize these models using conditional probability tables, and learning relies predominantly on local search heuristics such as Expectation Max-imization. Using tensor algebra, we propose an(More)
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