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» Learning of Boolean Functions Using Support Vector Machines
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ALT
2000
Springer
14 years 19 days ago
Computationally Efficient Transductive Machines
In this paper1 we propose a new algorithm for providing confidence and credibility values for predictions on a multi-class pattern recognition problem which uses Support Vector mac...
Craig Saunders, Alexander Gammerman, Volodya Vovk
ISMIR
2004
Springer
118views Music» more  ISMIR 2004»
14 years 2 months ago
Learning to Align Polyphonic Music
We describe an efficient learning algorithm for aligning a symbolic representation of a musical piece with its acoustic counterpart. Our method employs a supervised learning appr...
Shai Shalev-Shwartz, Joseph Keshet, Yoram Singer
IPM
2008
100views more  IPM 2008»
13 years 9 months ago
Query-level loss functions for information retrieval
Many machine learning technologies such as support vector machines, boosting, and neural networks have been applied to the ranking problem in information retrieval. However, since...
Tao Qin, Xu-Dong Zhang, Ming-Feng Tsai, De-Sheng W...
ICML
2003
IEEE
14 years 9 months ago
Transductive Learning via Spectral Graph Partitioning
We present a new method for transductive learning, which can be seen as a transductive version of the k nearest-neighbor classifier. Unlike for many other transductive learning me...
Thorsten Joachims
BIBE
2007
IEEE
162views Bioinformatics» more  BIBE 2007»
14 years 3 months ago
An Investigation into the Feasibility of Detecting Microscopic Disease Using Machine Learning
— The prognosis for many cancers could be improved dramatically if they could be detected while still at the microscopic disease stage. We are investigating the possibility of de...
Mary Qu Yang, Jack Y. Yang