MSRI Workshop on Nonlinear Estimation and Classification, The Boosting Approach to Machine Learning An Overview Robert E. Schapire AT&T Labs ; Research

Source URL: web.cs.hacettepe.edu.tr

Nonlinear Estimation and Classification, Springer, The Boosting Approach to Machine Learning An Overview Robert E. Schapire AT&T Labs Research

Source URL: www.lira.dist.unige.it

• Artificial intelligence
• Statistical classification
• AdaBoost
• Boosting
• LogitBoost
• Computational learning theory
• Binary classification
• Generalization error
• Multiclass classification
• Machine learning
• Ensemble learning
• Statistics

Jordan Boyd-Graber, Christiane Fellbaum, Daniel Osherson, and Robert Schapire. Adding Dense, Weighted, Connections to WordNet. Proceedings of the Global WordNet Conference, 2006. @inproceedings{Boyd-Graber:Fellbaum:Osher

Source URL: www.umiacs.umd.edu

• Parts of speech
• Grammar
• Knowledge representation
• WordNet
• Word-sense disambiguation
• Semantic similarity
• Semantic network
• Hyponymy
• Noun
• Linguistics
• Computational linguistics
• Lexical semantics

CLOOSTING: CLustering Data with bOOSTING F. Smeraldi1 , M. Bicego2,3 , M. Cristani2,3 , and V. Murino2,3 1 2

Source URL: profs.sci.univr.it

• Computational statistics
• AdaBoost
• Boosting
• LPBoost
• Cluster analysis
• K-means clustering
• Spectral clustering
• Yoav Freund
• Robert Schapire
• Machine learning
• Statistics
• Ensemble learning

Exploiting Spatial Information to Improve fMRI Pattern Classification Melissa K. Carroll , Kenneth A. Norman , James V. Haxby , Robert E. Schapire 1

Source URL: compmem.princeton.edu

• Computational statistics
• AdaBoost
• Boosting
• Statistical classification
• Classifier
• Functional magnetic resonance imaging
• Boosting methods for object categorization
• Ensemble learning
• Artificial intelligence
• Learning

Combining Spatial and Telemetric Features for Learning Animal Movement Models Berk Kapicioglu (Princeton University), Robert E. Schapire (Princeton University), Martin Wikelski (Max Planck Institute for Ornithology), Tam

Source URL: www.berkkapicioglu.com

• Missing data
• Random walk
• Statistics
• Estimation theory
• Expectation–maximization algorithm

Combining Spatial and Telemetric Features for Learning Animal Movement Models Berk Kapicioglu Robert E. Schapire Princeton University

Source URL: www.berkkapicioglu.com

• Maximum likelihood
• Stochastic optimization
• M-estimator
• Statistics
• Estimation theory
• Expectation–maximization algorithm

Boosting and Rocchio Applied to Text Filtering Robert E. Schapire, Yoram Singer, Amit Singhal AT&T Labs — Research 180 Park Avenue, Florham Park, NJ[removed]fschapire,singer,[removed] Abstract

Source URL: singhal.info

• Information
• Natural language processing
• Ensemble learning
• AdaBoost
• Machine learning
• Relevance feedback
• Boosting
• Precision and recall
• Vector space model
• Information science
• Information retrieval
• Science

Adding Dense, Weighted Connections to WordNet Jordan Boyd-Graber and Christiane Fellbaum and Daniel Osherson and Robert Schapire Princeton University, [removed] Abstract WORDNET, a ubiquitous tool for natural lan

Source URL: semanticweb.kaist.ac.kr

• WordNet
• Piek Vossen
• Word-sense disambiguation
• Semantic similarity
• Semantic network
• Lexical database
• Synonym ring
• Hyponymy
• Word sense
• Linguistics
• Computational linguistics
• Science

Journal of Japanese Society for Artificial Intelligence, 14(5):[removed], September, [removed]In Japanese, translation by Naoki Abe.) A Short Introduction to Boosting Yoav Freund Robert E. Schapire

Source URL: www.site.uottawa.ca

• Boosting
• Yoav Freund
• Decision stump
• Support vector machine
• Statistical classification
• Linear classifier
• BrownBoost
• Margin classifier
• Machine learning
• Ensemble learning
• AdaBoost