2026-09-20T03:53:01Z https://www.ideals.illinois.edu/oai-pmh

oai:www.ideals.illinois.edu:2142/78437 2023-07-11 col_2142_5131 col_2142_10761 com_2142_5130 com_2142_10755 com_2142_234

Selective Learning Algorithm Made available in DSpace on 2015-07-22T22:17:14Z (GMT). No. of bitstreams: 2 CHANG-DISSERTATION-2015.pdf: 1718796 bytes, checksum: acb2f0fcac6237b94e5733d5534763cb (MD5) LICENSE.txt: 4210 bytes, checksum: 781f641005bc15b659d6f1cee238b5c2 (MD5) Previous issue date: 2015-04-23 application/pdf Roth, Dan Roth, Dan Forsyth, David A. Zhai, ChengXiang Platt, John Chang, Kai-Wei 2015-07-22T22:17:14Z 2015-07-22T22:17:14Z 2015-05 2015-04-23 The desired output in many machine learning tasks is a structured object, such as tree, clustering, or sequence. Learning accurate prediction models for such problems requires training on large amounts of data, making use of expressive features and performing global inference that simultaneously assigns values to all interrelated nodes in the structure. All these contribute to significant scalability problems. In this thesis, we describe a collection of results that address several aspects of these problems – by carefully selecting and caching samples, structures, or latent items. Our results lead to efficient learning algorithms for large-scale binary classification models, structured prediction models and for online clustering models which, in turn, support reduction in problem size, improvements in training and evaluation speed and improved performance. We have used our algorithms to learn expressive models from large amounts of annotated data and achieve state-of-the art performance on several natural language processing tasks. Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2015-07-22 without embargo terms The student, Kai-Wei Chang, accepted the attached license on 2015-04-21 at 09:30. The student, Kai-Wei Chang, submitted this Dissertation for approval on 2015-04-21 at 09:40. This Dissertation was approved for publication on 2015-04-23 at 15:15. DSpace SAF Submission Ingestion Package generated from Vireo submission #7978 on 2015-07-22 at 10:33:02 http://hdl.handle.net/2142/78437 en Copyright 2015 Kai-Wei Chang Machine Learning Structured Learning Large-Scale Learning Selective algorithms for large-scale classification and structured learning text text 2015-5 Computer Science Computer Science University of Illinois at Urbana-Champaign Dissertation Ph.D.