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» Evaluating learning algorithms and classifiers
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CVPR
2010
IEEE
15 years 9 months ago
Far-Sighted Active Learning on a Budget for Image and Video Recognition
Active learning methods aim to select the most informative unlabeled instances to label first, and can help to focus image or video annotations on the examples that will most impr...
Sudheendra Vijayanarasimhan, Prateek Jain, Kristen...
101
Voted
CICLING
2005
Springer
15 years 6 months ago
A Machine Learning Approach to Information Extraction
Information extraction is concerned with applying natural language processing to automatically extract the essential details from text documents. A great disadvantage of current ap...
Alberto Téllez-Valero, Manuel Montes-y-G&oa...
MM
2004
ACM
142views Multimedia» more  MM 2004»
15 years 6 months ago
Learning query-class dependent weights in automatic video retrieval
Combining retrieval results from multiple modalities plays a crucial role for video retrieval systems, especially for automatic video retrieval systems without any user feedback a...
Rong Yan, Jun Yang 0003, Alexander G. Hauptmann
94
Voted
CEAS
2004
Springer
15 years 6 months ago
Learning to Extract Signature and Reply Lines from Email
: We describe methods for automatically identifying signature blocks and reply lines in plaintext email messages. This analysis has many potential applications, such as preprocessi...
Vitor Rocha de Carvalho, William W. Cohen
81
Voted
AAAI
2010
15 years 2 months ago
Assisting Users with Clustering Tasks by Combining Metric Learning and Classification
Interactive clustering refers to situations in which a human labeler is willing to assist a learning algorithm in automatically clustering items. We present a related but somewhat...
Sumit Basu, Danyel Fisher, Steven M. Drucker, Hao ...