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» Support Vector Machines: Theory and Applications
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NIPS
2001
15 years 1 months ago
Algorithmic Luckiness
Classical statistical learning theory studies the generalisation performance of machine learning algorithms rather indirectly. One of the main detours is that algorithms are studi...
Ralf Herbrich, Robert C. Williamson
ISMIR
2005
Springer
206views Music» more  ISMIR 2005»
15 years 5 months ago
Improving Content-Based Similarity Measures by Training a Collaborative Model
We observed that for multimedia data – especially music - collaborative similarity measures perform much better than similarity measures derived from content-based sound feature...
Richard Stenzel, Thomas Kamps
TCS
2008
14 years 11 months ago
Kernel methods for learning languages
This paper studies a novel paradigm for learning formal languages from positive and negative examples which consists of mapping strings to an appropriate highdimensional feature s...
Leonid Kontorovich, Corinna Cortes, Mehryar Mohri
KDD
2004
ACM
330views Data Mining» more  KDD 2004»
16 years 8 days ago
Learning to detect malicious executables in the wild
In this paper, we describe the development of a fielded application for detecting malicious executables in the wild. We gathered 1971 benign and 1651 malicious executables and enc...
Jeremy Z. Kolter, Marcus A. Maloof
CVPR
2009
IEEE
1528views Computer Vision» more  CVPR 2009»
16 years 4 months ago
Structured Output-Associative Regression
Structured outputs such as multidimensional vectors or graphs are frequently encountered in real world pattern recognition applications such as computer vision, natural language pr...
Liefeng Bo and Cristian Sminchisescu