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» Machine Learning by Function Decomposition
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CVPR
2003
IEEE
16 years 3 months ago
Kernel Principal Angles for Classification Machines with Applications to Image Sequence Interpretation
We consider the problem of learning with instances defined over a space of sets of vectors. We derive a new positive definite kernel f(A B) defined over pairs of matrices A B base...
Lior Wolf, Amnon Shashua
ICML
2007
IEEE
16 years 2 months ago
Learning to combine distances for complex representations
The k-Nearest Neighbors algorithm can be easily adapted to classify complex objects (e.g. sets, graphs) as long as a proper dissimilarity function is given over an input space. Bo...
Adam Woznica, Alexandros Kalousis, Melanie Hilario
ICML
2007
IEEE
16 years 2 months ago
Learning nonparametric kernel matrices from pairwise constraints
Many kernel learning methods have to assume parametric forms for the target kernel functions, which significantly limits the capability of kernels in fitting diverse patterns. Som...
Steven C. H. Hoi, Rong Jin, Michael R. Lyu
117
Voted
ICALT
2008
IEEE
15 years 8 months ago
Learning Application Suite Creating and Playing SCORM Compatible Web and Computer Based Training
In the process of developing Web Based Training (WBT) applications, the Sharable Content Object Reference Model (SCORM) has become the most common eLearning standard making it pos...
Marco Nordmann, Jens Neumann
101
Voted
COLT
1998
Springer
15 years 6 months ago
Robust Learning Aided by Context
Empirical studies of multitask learning provide some evidence that the performance of a learning system on its intended targets improves by presenting to the learning system relat...
John Case, Sanjay Jain, Matthias Ott, Arun Sharma,...