'Uncertainty sampling' diaporamas de présentation

Active and Proactive Machine Learning: From Fundamentals to Applications

Active and Proactive Machine Learning: From Fundamentals to Applications. Jaime Carbonell (www.cs.cmu.edu/~jgc) With Pinar Donmez , Jingui He, Vamshi Ambati , Oznur Tastan , Xi Chen Language Technologies Inst. & Machine Learning Dept. Carnegie Mellon University 26 March 2010.

787 views • 64 slides

Re-active Learning : Active Learning with Re-labeling

Re-active Learning : Active Learning with Re-labeling. Christopher H. Lin University of Washington Mausam IIT Delhi Daniel S. Weld University of Washington. *Speaker not paid by Oracle Corporation. CROWDSOURCING. (Labeling) Mistakes Were M ade. Human. Majority Vote. Parrot.

523 views • 52 slides

Active Learning: Class Questions

566 views • 39 slides

Active Learning

641 views • 27 slides

Active Learning 02-750

Active Learning 02-750. Jaime Carbonell , Language Technologies Institute Carnegie Mellon University www.cs.cmu.edu/~{jgc | pinard | jinruih | vamshi} 22 September 2010. Why is Active Learning Important?. Labeled data volumes ?? unlabeled data volumes

437 views • 25 slides

Using Web Structure for Classifying and Describing Web Pages

Using Web Structure for Classifying and Describing Web Pages. Eric J. Glover 1 , Kostas Tsioutsiouliklis 1,2 , Steve Lawrence 1 , David M. Pennock 1 , Gary W. Flake 1 International World Wide Web Conference, 2002 Presented by Zaihan Yang CSE Web Mining. Introduction. Aim

274 views • 15 slides