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CORR
2010
Springer
193views Education» more  CORR 2010»
15 years 5 months ago
A Probabilistic Approach for Learning Folksonomies from Structured Data
Learning structured representations has emerged as an important problem in many domains, including document and Web data mining, bioinformatics, and image analysis. One approach t...
Anon Plangprasopchok, Kristina Lerman, Lise Getoor
AIRS
2010
Springer
15 years 4 months ago
Learning to Rank with Supplementary Data
This paper is concerned with a new task of ranking, referred to as "supplementary data assisted ranking", or "supplementary ranking" for short. Different from c...
Wenkui Ding, Tao Qin, Xu-Dong Zhang
BMCBI
2010
140views more  BMCBI 2010»
15 years 4 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
IJPP
2011
115views more  IJPP 2011»
14 years 10 months ago
Milepost GCC: Machine Learning Enabled Self-tuning Compiler
Tuning compiler optimizations for rapidly evolving hardware makes porting and extending an optimizing compiler for each new platform extremely challenging. Iterative optimization i...
Grigori Fursin, Yuriy Kashnikov, Abdul Wahid Memon...
WSDM
2012
ACM
267views Data Mining» more  WSDM 2012»
14 years 2 months ago
Learning to rank with multi-aspect relevance for vertical search
Many vertical search tasks such as local search focus on specific domains. The meaning of relevance in these verticals is domain-specific and usually consists of multiple well-d...
Changsung Kang, Xuanhui Wang, Yi Chang, Belle L. T...