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ICML
2004
IEEE
16 years 7 months ago
Multiple kernel learning, conic duality, and the SMO algorithm
While classical kernel-based classifiers are based on a single kernel, in practice it is often desirable to base classifiers on combinations of multiple kernels. Lanckriet et al. ...
Francis R. Bach, Gert R. G. Lanckriet, Michael I. ...
KDD
2009
ACM
178views Data Mining» more  KDD 2009»
16 years 7 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
CHI
2001
ACM
16 years 7 months ago
Locus of feedback control in computer-based tutoring: impact on learning rate, achievement and attitudes
The advent of second-generation intelligent computer tutors raises an important instructional design question: when should tutorial advice be presented in problem solving? This pa...
Albert T. Corbett, John R. Anderson
161
Voted
WEBI
2009
Springer
16 years 1 months ago
Learning Deep Web Crawling with Diverse Features
—The key to Deep Web crawling is to submit promising keywords to query form and retrieve Deep Web content efficiently. To select keywords, existing methods make a decision based ...
Lu Jiang, Zhaohui Wu, Qinghua Zheng, Jun Liu
GECCO
2009
Springer
194views Optimization» more  GECCO 2009»
16 years 1 months ago
Combining evolution strategy and gradient descent method for discriminative learning of bayesian classifiers
The optimization method is one of key issues in discriminative learning of pattern classifiers. This paper proposes a hybrid approach of the Covariance Matrix Adaptation Evolution...
Xuefeng Chen, Xiabi Liu, Yunde Jia