Chiung-min Tsai

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We develop a new static index pruning criterion based on the notion of information preservation. This idea is motivated by the fact that model degeneration, as does static index pruning, inevitably reduces the predictive power of the resulting model. We model this loss in predictive power using conditional entropy and show that the decision in static index(More)
Languages are constantly evolving through their users due to the need to communicate more efficiently. Under this hypothesis, we formulate unsupervised word segmentation as a regularized compression process. We reduce this process to an optimization problem, and propose a greedy inclusion solution. Preliminary test results on the Bernstein-Ratner corpus and(More)
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