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ICDM
2010
IEEE
122views Data Mining» more  ICDM 2010»
15 years 2 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....
AAAI
2006
15 years 5 months ago
Multiclass Support Vector Machines for Articulatory Feature Classification
of somewhat abstracting away from the literal physiological measurements of articulation that are so closely tied to the acoustic signal, and with some additional computational bur...
Brian Hutchinson, Jianna Zhang
ICDM
2009
IEEE
154views Data Mining» more  ICDM 2009»
15 years 2 months ago
GSML: A Unified Framework for Sparse Metric Learning
There has been significant recent interest in sparse metric learning (SML) in which we simultaneously learn both a good distance metric and a low-dimensional representation. Unfor...
Kaizhu Huang, Yiming Ying, Colin Campbell
KDD
2006
ACM
130views Data Mining» more  KDD 2006»
16 years 4 months ago
Efficient anonymity-preserving data collection
The output of a data mining algorithm is only as good as its inputs, and individuals are often unwilling to provide accurate data about sensitive topics such as medical history an...
Justin Brickell, Vitaly Shmatikov
COLT
2008
Springer
15 years 6 months ago
Does Unlabeled Data Provably Help? Worst-case Analysis of the Sample Complexity of Semi-Supervised Learning
We study the potential benefits to classification prediction that arise from having access to unlabeled samples. We compare learning in the semi-supervised model to the standard, ...
Shai Ben-David, Tyler Lu, Dávid Pál