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» A Theory for Memory-Based Learning
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ICML
2003
IEEE
16 years 5 months ago
Semi-Supervised Learning Using Gaussian Fields and Harmonic Functions
An approach to semi-supervised learning is proposed that is based on a Gaussian random field model. Labeled and unlabeled data are represented as vertices in a weighted graph, wit...
Xiaojin Zhu, Zoubin Ghahramani, John D. Lafferty
ATAL
2006
Springer
15 years 8 months ago
Learning to identify winning coalitions in the PAC model
We consider PAC learning of simple cooperative games, in which the coalitions are partitioned into "winning" and "losing" coalitions. We analyze the complexity...
Ariel D. Procaccia, Jeffrey S. Rosenschein
138
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FLAIRS
2004
15 years 6 months ago
VENUS: A System for Novelty Detection in Video Streams with Learning
Novelty detection in video is a rapidly developing application domain within computer vision. The motivation behind this paper is a learning based framework for detecting novelty ...
Roger S. Gaborski, Vishal S. Vaingankar, Vineet Ch...
CORR
2010
Springer
92views Education» more  CORR 2010»
15 years 5 months ago
Hardness Results for Agnostically Learning Low-Degree Polynomial Threshold Functions
Hardness results for maximum agreement problems have close connections to hardness results for proper learning in computational learning theory. In this paper we prove two hardnes...
Ilias Diakonikolas, Ryan O'Donnell, Rocco A. Serve...
LATA
2009
Springer
15 years 11 months ago
Hypothesis Spaces for Learning
In this paper we survey some results in inductive inference showing how learnability of a class of languages may depend on hypothesis space chosen. We also discuss results which co...
Sanjay Jain