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Showing below up to 20 results in range #21 to #40.

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  1. (hist) ‎MRS Guinea Pig ‎[11,340 bytes]
  2. (hist) ‎Machine Learning 10-601 in Fall 2014 ‎[11,297 bytes]
  3. (hist) ‎Recent or influential technical papers in Analysis of Social Media ‎[11,164 bytes]
  4. (hist) ‎Das Sarma et. al., Dynamic Relationship and Event Discovery, WSDM 2011 ‎[11,086 bytes]
  5. (hist) ‎Controversial events detection ‎[10,989 bytes]
  6. (hist) ‎Eisenstein et al ACL 2011. Discovering Sociolinguistic Associations with Structured Sparsity ‎[10,726 bytes]
  7. (hist) ‎Park et al CSCW 2011. The Politics of Comments: Predicting Political Orientation of News Stories with Commenters’ Sentiment Patterns ‎[10,574 bytes]
  8. (hist) ‎Inferring Social Ties From Geographic Coincidences ‎[10,490 bytes]
  9. (hist) ‎Ahn and Dabbish, Labeling images with a computer game, SIGCHI, Vienna, Austria: ACM, 2004, pp. 319-326. ‎[10,416 bytes]
  10. (hist) ‎Talukdar 2006 a context pattern induction method for named entity extraction ‎[10,338 bytes]
  11. (hist) ‎Daume ICML 2009 ‎[10,331 bytes]
  12. (hist) ‎Reisinger et al 2010: Spherical Topic Models ‎[10,266 bytes]
  13. (hist) ‎Adamic, Zhang, Bakshy, and Ackerman, Knowledge Sharing and Yahoo Answers: Everyone Knows Something, WWW 2008 ‎[10,257 bytes]
  14. (hist) ‎Domain-Assisted Product Aspect Hierarchy Generation: Towards Hierarchical Organization of Unstructured Consumer Reviews ‎[10,227 bytes]
  15. (hist) ‎Denis and Muller, Predicting Globally-Coherent Temporal Structures from Texts via Endpoint Inference and Graph Decomposition, IJCAI 2011 ‎[9,456 bytes]
  16. (hist) ‎Structured Output Learning with Indirect Supervision ‎[9,324 bytes]
  17. (hist) ‎Machine Learning 10-601 in Fall 2013 ‎[9,281 bytes]
  18. (hist) ‎Projects for Machine Learning with Large Datasets 10-605 in Spring 2012 ‎[9,200 bytes]
  19. (hist) ‎Syllabus for Machine Learning with Large Datasets 10-605 in Fall 2017 ‎[9,125 bytes]
  20. (hist) ‎Syllabus for Machine Learning with Large Datasets 10-605 in Spring 2015 ‎[9,104 bytes]

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