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» Generalization Bounds for Learning Kernels
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PR
2010
163views more  PR 2010»
13 years 8 months ago
Optimal feature selection for support vector machines
Selecting relevant features for Support Vector Machine (SVM) classifiers is important for a variety of reasons such as generalization performance, computational efficiency, and ...
Minh Hoai Nguyen, Fernando De la Torre
UAI
2004
13 years 11 months ago
The Minimum Information Principle for Discriminative Learning
Exponential models of distributions are widely used in machine learning for classification and modelling. It is well known that they can be interpreted as maximum entropy models u...
Amir Globerson, Naftali Tishby
ML
2012
ACM
385views Machine Learning» more  ML 2012»
12 years 5 months ago
An alternative view of variational Bayes and asymptotic approximations of free energy
Bayesian learning, widely used in many applied data-modeling problems, is often accomplished with approximation schemes because it requires intractable computation of the posterio...
Kazuho Watanabe
AII
1992
14 years 1 months ago
Learning from Multiple Sources of Inaccurate Data
Most theoretical models of inductive inference make the idealized assumption that the data available to a learner is from a single and accurate source. The subject of inaccuracies ...
Ganesh Baliga, Sanjay Jain, Arun Sharma
SIGCSE
2004
ACM
141views Education» more  SIGCSE 2004»
14 years 3 months ago
Running on the bare metal with GeekOS
Undergraduate operating systems courses are generally taught e of two approaches: abstract or concrete. In the approach, students learn the concepts underlying operating systems t...
David Hovemeyer, Jeffrey K. Hollingsworth, Bobby B...