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• Weka
  .... Weka contains tools for data pre-processing, classification, regression, clustering, association rules, and visualization. It is also well-suited for developin
  540 bytes (85 words) - 20:09, 26 September 2012
• K-means
  ...the data as well as in the iterative refinement approach employed by both algorithms. ...>), where each observation is a ''d''-dimensional real vector, ''k''-means clustering aims to partition the ''n'' observations into ''k'' sets (''k'' ≤ ''n'')
  1 KB (190 words) - 23:02, 27 March 2011
• Class meeting for 10-605 SSL on Graphs
  ...in and William W. Cohen (2010)]: Semi-Supervised Classification of Network Data Using Very Few Labels in ASONAM-2010. ...nars/docs/BinderPartha.pdf PP Talukdar, K Crammer (2009):] New regularized algorithms for transductive learning Machine Learning and Knowledge Discovery in Datab
  2 KB (214 words) - 11:20, 14 November 2017
• Class meeting for 10-405 SSL on Graphs
  ...in and William W. Cohen (2010)]: Semi-Supervised Classification of Network Data Using Very Few Labels in ASONAM-2010. ...nars/docs/BinderPartha.pdf PP Talukdar, K Crammer (2009):] New regularized algorithms for transductive learning Machine Learning and Knowledge Discovery in Datab
  2 KB (231 words) - 09:50, 30 March 2018
• Lin and Wu. 2009. Phrase Clustering for Discriminative Learning.
  ...ng| coauthors = X. Wu| date = 2009| first = D.| last = Lin| title = Phrase clustering for discriminative learning| url = http://www.aclweb.org/anthology/P/P09/P0 This paper makes use of phrase [[UsesMethod::clustering]] to improve on the state of the art for the [[AddressesProblem::Named Enti
  4 KB (577 words) - 00:07, 30 September 2011
• Barzilay and Elhadad, 2003
  The approach used here is has multiple components, first clustering paragraphs within-corpus, then aligning documents at the paragraph level (e == Algorithms ==
  5 KB (807 words) - 07:10, 30 September 2011
• Automated Template Extraction
  ...would be beneficial if we could automatically produce these templates from data. ...ur most often in the data is one way, while we could also use more complex clustering like Chambers and Jurafsky.
  4 KB (707 words) - 21:45, 6 October 2011
• Huang et al, ACL 2009: Profile Based Cross-Document Coreference Using Kernelized Fuzzy Relational Clustering
  ...Profile Based Cross-Document Coreference Using Kernelized Fuzzy Relational Clustering. In Proceedings of the 47th Annual Meeting of the ACL and the 4th IJCNLP of ...ce function, and finally clustering them using kernelized fuzzy relational clustering.
  5 KB (765 words) - 00:45, 1 December 2010
• Class Meeting for 10-710 09-22-2011
  ...g Methods for Hidden Markov Models: Theory and Experiments with Perceptron Algorithms, Collins, EMNLP 2002]. ...= A.| last = Globerson| pages = 305–312| title = Exponentiated gradient algorithms for log-linear structured prediction}}]]. A more recent EG-based approach.
  2 KB (291 words) - 15:39, 22 September 2011
• Class Meeting for 10-707 10/6/2010
  ...g Methods for Hidden Markov Models: Theory and Experiments with Perceptron Algorithms, Collins, EMNLP 2002]. ...= A.| last = Globerson| pages = 305–312| title = Exponentiated gradient algorithms for log-linear structured prediction}}]]. A more recent EG-based approach.
  2 KB (279 words) - 09:22, 4 October 2010
• Machine Learning with Large Datasets 10-605
  ...he project will be designed to compare the scalability of variant learning algorithms on datasets. * Streaming learning algorithms
  5 KB (671 words) - 11:55, 14 November 2011
• Syllabus for Machine Learning with Large Datasets 10-605 in Fall 2016
  ...n Fall 2016 Overview|Overview]]. Grading policies and etc, History of Big Data, Complexity theory and cost of important operations ...5 in Fall 2016 Probability Review|Probability Review]]. Counting for big data and density estimation, streaming Naive Bayes, Rocchio and TFIDF
  7 KB (1,002 words) - 10:54, 11 August 2017
• Community structure in social and biological networks
  ...paper to assign the weight. Finally, an algorithm similar to hierarchical clustering is proposed and evaluated based on three computer-generated or real-word ne ...unity structure detection algorithm, similar to the iterative hierarchical clustering algorithm, can be formalized as follows:
  6 KB (875 words) - 23:11, 18 December 2012
• Su et al, 2008
  ...erimental results demonstrate that our method outperforms the state-of-art algorithms.
  2 KB (276 words) - 21:01, 1 October 2012
• Project - Second Draft Proposal - Bo, Kevin, Rushin
  Title: '''Fine & coarse grain clustering of tweets based on topics''' ...ce, and "Just for Fun". We propose to address problem by gathering twitter data for approximately 30 popular hash tags corresponding to the different topic
  5 KB (862 words) - 19:21, 14 February 2011
• Syllabus for Machine Learning with Large Datasets 10-605 in Fall 2017
  ...for 10-605 Overview|Overview]]. Grading policies and etc, History of Big Data, Complexity theory and cost of important operations ...ting for 10-605 Probability Review|Probability Review]]. Counting for big data and density estimation, streaming Naive Bayes, Rocchio and TFIDF
  9 KB (1,220 words) - 11:06, 28 November 2017
• Syllabus for Machine Learning with Large Datasets 10-405 in Spring 2018
  * Find a recent paper which includes data and an implementation for a non-trivial neural model in a standard framewor ...tion on CPUs. The architecture you should build should stream through the data, and construct multiple tasks which require a worker to perform a minibatch
  9 KB (1,249 words) - 12:46, 30 April 2018
• Syllabus for Machine Learning with Large Datasets 10-605 in Fall 2015
  * Tues Sep 8. [[Class meeting for 10-605 Streaming Naive Bayes|Streaming algorithms and Naive Bayes; The stream-and-sort design pattern; Naive Bayes for large ...10-605 Phrases_with_Stream_and_Sort|Implementing Phrase Finding and Large-Data Testing for Naive Bayes with Stream-and-Sort]].
  6 KB (908 words) - 09:07, 11 October 2016
• Dwijaya Social Media Analysis
  ...els. I have also worked previously on the area of opinion mining and graph clustering.
  3 KB (426 words) - 11:40, 8 September 2011
• Forum-Based Language Learning Analysis
  ...wledge propagation, and identifying influence. In this work we plan to use data from a forum dedicating to studying the Spanish language to facilitate lang ...nal unsupervised clustering techniques such as Yang & Meng's (2006) Markov clustering approach.
  6 KB (834 words) - 09:46, 15 February 2011

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