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ICDM
2010
IEEE
122views Data Mining» more  ICDM 2010»
15 years 4 months ago
Learning Preferences with Millions of Parameters by Enforcing Sparsity
We study the retrieval task that ranks a set of objects for a given query in the pairwise preference learning framework. Recently researchers found out that raw features (e.g. word...
Xi Chen, Bing Bai, Yanjun Qi, Qihang Lin, Jaime G....
ICDM
2010
IEEE
128views Data Mining» more  ICDM 2010»
15 years 4 months ago
User-Based Active Learning
Active learning has been proven a reliable strategy to reduce manual efforts in training data labeling. Such strategies incorporate the user as oracle: the classifier selects the m...
Christin Seifert, Michael Granitzer
ICMLA
2009
15 years 4 months ago
Transformation Learning Via Kernel Alignment
This article proposes an algorithm to automatically learn useful transformations of data to improve accuracy in supervised classification tasks. These transformations take the for...
Andrew Howard, Tony Jebara
PAMI
2011
15 years 1 months ago
Semi-Supervised Learning via Regularized Boosting Working on Multiple Semi-Supervised Assumptions
—Semi-supervised learning concerns the problem of learning in the presence of labeled and unlabeled data. Several boosting algorithms have been extended to semi-supervised learni...
Ke Chen, Shihai Wang
IFIP
2010
Springer
15 years 1 months ago
Combining Software and Hardware LCS for Lightweight On-Chip Learning
In this paper we present a novel two-stage method to realize a lightweight but very capable hardware implementation of a Learning Classifier System for on-chip learning. Learning C...
Andreas Bernauer, Johannes Zeppenfeld, Oliver Brin...