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AIRS
2010
Springer
13 years 7 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
IJPP
2011
115views more  IJPP 2011»
13 years 23 days 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»
12 years 4 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...
ISM
2006
IEEE
113views Multimedia» more  ISM 2006»
14 years 3 months ago
Individualization and Flexibility through Computer Algebra Systems in Virtual Laboratories
Virtual labs enable field specific experiments and open them for collaborative and distributed usage. In order to realize comprehensive laboratory set-ups providing a scientifi...
Sabina Jeschke, Thomas Richter
CVPR
2009
IEEE
15 years 4 months ago
Learning To Detect Unseen Object Classes by Between-Class Attribute Transfer
We study the problem of object classification when training and test classes are disjoint, i.e. no training examples of the target classes are available. This setup has hardly be...
Christoph H. Lampert, Hannes Nickisch, Stefan Harm...