منابع مشابه
Vine Pruning for Efficient Multi-Pass Dependency Parsing
Coarse-to-fine inference has been shown to be a robust approximate method for improving the efficiency of structured prediction models while preserving their accuracy. We propose a multi-pass coarse-to-fine architecture for dependency parsing using linear-time vine pruning and structured prediction cascades. Our first-, second-, and third-order models achieve accuracies comparable to those of t...
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A Vine Estimation of Distribution Algorithm (VEDA) is a recently proposed optimization procedure built on top of a probabilistic graphical model called vine. The rst target of vines was uncertainty analysis with high dimensional dependence modeling. The aim of this communication is to draw a path through a simple set of experiments, from the Univariate Marginal Distribution Algorithm to VEDA. F...
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ژورنال
عنوان ژورنال: Kvasny Prumysl
سال: 1955
ISSN: 0023-5830
DOI: 10.18832/kp1955021