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We present a novel semi-supervised training algorithm for learning dependency parsers. By combining a supervised large margin loss with an unsupervised least squares loss, a dis-criminative, convex, semi-supervised learning algorithm can be obtained that is applicable to large-scale problems. To demonstrate the benefits of this approach, we apply the(More)
Recently, significant progress has been made on learning structured predictors via coordinated training algorithms such as conditional random fields and maximum margin Markov networks. Unfortunately , these techniques are based on specialized training algorithms, are complex to implement, and expensive to run. We present a much simpler approach to training(More)
We present an improved approach for learning dependency parsers from tree-bank data. Our technique is based on two ideas for improving large margin training in the context of dependency parsing. First, we incorporate local constraints that enforce the correctness of each individual link, rather than just scoring the global parse tree. Second, to cope with(More)
My research is focused on developing machine learning algorithms for inferring dependency parsers from language data. By investigating several approaches I have developed a unifying perspective that allows me to share advances between both probabilistic and non-probabilistic methods. First, I describe a generative technique that uses a strictly lexicalised(More)
Data-driven (statistical) approaches have been playing an increasingly prominent role in parsing since the 1990s. In recent years, there has been a growing interest in dependency-based as opposed to constituency-based approaches to syntactic parsing, with application to a wide range of research areas and different languages. Graph-based and transition-based(More)
Since the reduced forms of the popular measures of asymmetric information in the price formation process are not nested within larger models we cannot evaluate their fit using standard statistical tools. Furthermore, pairwise correlations amongst the measures are small. We benchmark these measures cross-sectionally to realized specialist loss rates (using(More)
Permission is hereby granted to the University of Alberta Library to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. The author reserves all other publication and other rights in association with the copyright in the thesis, and except as herein before provided, neither the(More)
The paper employs the model of growth drag of resources during urbanization process with the neo-classic growth theory and relationship function between urbanization and economic growth, and takes Jiangxi province as an empirical case. The results show that the drags of water and land during urbanization process in Jiangxi province respectively are(More)