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» A Bayesian Metric for Evaluating Machine Learning Algorithms
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TKDE
2010
182views more  TKDE 2010»
14 years 10 months ago
MILD: Multiple-Instance Learning via Disambiguation
In multiple-instance learning (MIL), an individual example is called an instance and a bag contains a single or multiple instances. The class labels available in the training set ...
Wu-Jun Li, Dit-Yan Yeung
MM
2010
ACM
137views Multimedia» more  MM 2010»
15 years 17 days ago
Self-diagnostic peer-assisted video streaming through a learning framework
Quality control and resource optimization are challenging problems in peer-assisted video streaming systems, due to their large scales and unreliable peer behavior. Such systems a...
Di Niu, Baochun Li, Shuqiao Zhao
WSDM
2010
ACM
204views Data Mining» more  WSDM 2010»
15 years 7 months ago
Learning URL patterns for webpage de-duplication
Presence of duplicate documents in the World Wide Web adversely affects crawling, indexing and relevance, which are the core building blocks of web search. In this paper, we pres...
Hema Swetha Koppula, Krishna P. Leela, Amit Agarwa...
CIKM
2008
Springer
15 years 2 months ago
To swing or not to swing: learning when (not) to advertise
Web textual advertising can be interpreted as a search problem over the corpus of ads available for display in a particular context. In contrast to conventional information retrie...
Andrei Z. Broder, Massimiliano Ciaramita, Marcus F...
GECCO
2006
Springer
151views Optimization» more  GECCO 2006»
15 years 4 months ago
Sporadic model building for efficiency enhancement of hierarchical BOA
This paper describes and analyzes sporadic model building, which can be used to enhance the efficiency of the hierarchical Bayesian optimization algorithm (hBOA) and other advance...
Martin Pelikan, Kumara Sastry, David E. Goldberg