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» Probabilistic topic modeling for genomic data interpretation
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UAI
2003
15 years 1 months ago
Collaborative Ensemble Learning: Combining Collaborative and Content-Based Information Filtering via Hierarchical Bayes
Collaborative filtering (CF) and contentbased filtering (CBF) have widely been used in information filtering applications, both approaches having their individual strengths and...
Kai Yu, Anton Schwaighofer, Volker Tresp, Wei-Ying...
97
Voted
WWW
2008
ACM
16 years 10 days ago
Spatial variation in search engine queries
Local aspects of Web search -- associating Web content and queries with geography -- is a topic of growing interest. However, the underlying question of how spatial variation is m...
Lars Backstrom, Jon M. Kleinberg, Ravi Kumar, Jasm...
90
Voted
ICML
2010
IEEE
15 years 22 days ago
Proximal Methods for Sparse Hierarchical Dictionary Learning
We propose to combine two approaches for modeling data admitting sparse representations: on the one hand, dictionary learning has proven effective for various signal processing ta...
Rodolphe Jenatton, Julien Mairal, Guillaume Obozin...
116
Voted
ECIR
2008
Springer
15 years 1 months ago
Filaments of Meaning in Word Space
Word space models, in the sense of vector space models built on distributional data taken from texts, are used to model semantic relations between words. We argue that the high dim...
Jussi Karlgren, Anders Holst, Magnus Sahlgren
103
Voted
PKDD
2010
Springer
160views Data Mining» more  PKDD 2010»
14 years 10 months ago
Entropy and Margin Maximization for Structured Output Learning
Abstract. We consider the problem of training discriminative structured output predictors, such as conditional random fields (CRFs) and structured support vector machines (SSVMs)....
Patrick Pletscher, Cheng Soon Ong, Joachim M. Buhm...