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WSDM
2012
ACM
267views Data Mining» more  WSDM 2012»
12 years 17 days 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...
CVPR
2012
IEEE
11 years 7 months ago
Non-negative low rank and sparse graph for semi-supervised learning
Constructing a good graph to represent data structures is critical for many important machine learning tasks such as clustering and classification. This paper proposes a novel no...
Liansheng Zhuang, Haoyuan Gao, Zhouchen Lin, Yi Ma...
CORR
2012
Springer
214views Education» more  CORR 2012»
12 years 22 days ago
Stochastic Low-Rank Kernel Learning for Regression
We present a novel approach to learn a kernelbased regression function. It is based on the use of conical combinations of data-based parameterized kernels and on a new stochastic ...
Pierre Machart, Thomas Peel, Liva Ralaivola, Sandr...
AAAI
2012
11 years 7 months ago
Learning the Kernel Matrix with Low-Rank Multiplicative Shaping
Selecting the optimal kernel is an important and difficult challenge in applying kernel methods to pattern recognition. To address this challenge, multiple kernel learning (MKL) ...
Tomer Levinboim, Fei Sha
SIGIR
2012
ACM
11 years 7 months ago
Effect of dynamic pruning safety on learning to rank effectiveness
Craig Macdonald, Nicola Tonellotto, Iadh Ounis