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COLT
2005
Springer
13 years 9 months ago
Loss Bounds for Online Category Ranking
Category ranking is the task of ordering labels with respect to their relevance to an input instance. In this paper we describe and analyze several algorithms for online category r...
Koby Crammer, Yoram Singer
KDD
2009
ACM
178views Data Mining» more  KDD 2009»
14 years 8 months ago
Catching the drift: learning broad matches from clickthrough data
Identifying similar keywords, known as broad matches, is an important task in online advertising that has become a standard feature on all major keyword advertising platforms. Eff...
Sonal Gupta, Mikhail Bilenko, Matthew Richardson
JAIR
2007
114views more  JAIR 2007»
13 years 7 months ago
Marvin: A Heuristic Search Planner with Online Macro-Action Learning
This paper describes Marvin, a planner that competed in the Fourth International Planning Competition (IPC 4). Marvin uses action-sequence-memoisation techniques to generate macro...
Andrew Coles, Kate A. Smith
ICPR
2010
IEEE
13 years 5 months ago
Online Learning with Self-Organizing Maps for Anomaly Detection in Crowd Scenes
Detecting abnormal behaviors in crowd scenes is quite important for public security and has been paid more and more attentions. Most previous methods use offline trained model to p...
Jie Feng, Chao Zhang, Pengwei Hao
ETVC
2008
13 years 9 months ago
Intrinsic Geometries in Learning
In a seminal paper, Amari (1998) proved that learning can be made more efficient when one uses the intrinsic Riemannian structure of the algorithms' spaces of parameters to po...
Richard Nock, Frank Nielsen