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» Learning to Rank Using an Ensemble of Lambda-Gradient Models
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127
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SIGKDD
2010
128views more  SIGKDD 2010»
14 years 10 months ago
On cross-validation and stacking: building seemingly predictive models on random data
A number of times when using cross-validation (CV) while trying to do classification/probability estimation we have observed surprisingly low AUC's on real data with very few...
Claudia Perlich, Grzegorz Swirszcz
NIPS
2001
15 years 4 months ago
Global Coordination of Local Linear Models
High dimensional data that lies on or near a low dimensional manifold can be described by a collection of local linear models. Such a description, however, does not provide a glob...
Sam T. Roweis, Lawrence K. Saul, Geoffrey E. Hinto...
WSDM
2012
ACM
285views Data Mining» more  WSDM 2012»
13 years 10 months ago
Probabilistic models for personalizing web search
We present a new approach for personalizing Web search results to a specific user. Ranking functions for Web search engines are typically trained by machine learning algorithms u...
David Sontag, Kevyn Collins-Thompson, Paul N. Benn...
127
Voted
MM
2005
ACM
172views Multimedia» more  MM 2005»
15 years 8 months ago
Learning the semantics of multimedia queries and concepts from a small number of examples
In this paper we unify two supposedly distinct tasks in multimedia retrieval. One task involves answering queries with a few examples. The other involves learning models for seman...
Apostol Natsev, Milind R. Naphade, Jelena Tesic
AAAI
2008
15 years 5 months ago
Zero-data Learning of New Tasks
We introduce the problem of zero-data learning, where a model must generalize to classes or tasks for which no training data are available and only a description of the classes or...
Hugo Larochelle, Dumitru Erhan, Yoshua Bengio