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CIKM
2008
Springer
13 years 11 months ago
Are click-through data adequate for learning web search rankings?
Learning-to-rank algorithms, which can automatically adapt ranking functions in web search, require a large volume of training data. A traditional way of generating training examp...
Zhicheng Dou, Ruihua Song, Xiaojie Yuan, Ji-Rong W...
KDD
2008
ACM
161views Data Mining» more  KDD 2008»
14 years 9 months ago
Spectral domain-transfer learning
Traditional spectral classification has been proved to be effective in dealing with both labeled and unlabeled data when these data are from the same domain. In many real world ap...
Xiao Ling, Wenyuan Dai, Gui-Rong Xue, Qiang Yang, ...
BMCBI
2010
140views more  BMCBI 2010»
13 years 6 months ago
An improved machine learning protocol for the identification of correct Sequest search results
Background: Mass spectrometry has become a standard method by which the proteomic profile of cell or tissue samples is characterized. To fully take advantage of tandem mass spectr...
Morten Kallberg, Hui Lu
KDD
1995
ACM
85views Data Mining» more  KDD 1995»
14 years 26 days ago
Estimating the Robustness of Discovered Knowledge
This paper introduces a new measurement, robustness, to measure the quality of machine-discovered knowledge from real-world databases that change over time. A piece of knowledge i...
Chun-Nan Hsu, Craig A. Knoblock
ICML
2010
IEEE
13 years 10 months ago
Non-Local Contrastive Objectives
Pseudo-likelihood and contrastive divergence are two well-known examples of contrastive methods. These algorithms trade off the probability of the correct label with the probabili...
David Vickrey, Cliff Chiung-Yu Lin, Daphne Koller