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NIPS
2001
14 years 8 days ago
Efficiency versus Convergence of Boolean Kernels for On-Line Learning Algorithms
The paper studies machine learning problems where each example is described using a set of Boolean features and where hypotheses are represented by linear threshold elements. One ...
Roni Khardon, Dan Roth, Rocco A. Servedio
MLG
2007
Springer
14 years 5 months ago
A Universal Kernel for Learning Regular Languages
We give a universal kernel that renders all the regular languages linearly separable. We are not able to compute this kernel efficiently and conjecture that it is intractable, but...
Leonid Kontorovich
CSDA
2010
133views more  CSDA 2010»
13 years 8 months ago
Optimized fixed-size kernel models for large data sets
A modified active subset selection method based on quadratic R
Kris De Brabanter, Jos De Brabanter, Johan A. K. S...
SIGKDD
2010
183views more  SIGKDD 2010»
13 years 5 months ago
Inactive learning?: difficulties employing active learning in practice
Despite the tremendous level of adoption of machine learning techniques in real-world settings, and the large volume of research on active learning, active learning techniques hav...
Josh Attenberg, Foster J. Provost
CVPR
2005
IEEE
15 years 27 days ago
A Semi-Supervised Active Learning Framework for Image Retrieval
Although recent studies have shown that unlabeled data are beneficial to boosting the image retrieval performance, very few approaches for image retrieval can learn with labeled a...
Steven C. H. Hoi, Michael R. Lyu