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» Learning Bounds for Domain Adaptation
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ICML
2010
IEEE
13 years 8 months ago
OTL: A Framework of Online Transfer Learning
In this paper, we investigate a new machine learning framework called Online Transfer Learning (OTL) that aims to transfer knowledge from some source domain to an online learning ...
Peilin Zhao, Steven C. H. Hoi
COLT
2008
Springer
13 years 9 months ago
Dimension and Margin Bounds for Reflection-invariant Kernels
A kernel over the Boolean domain is said to be reflection-invariant, if its value does not change when we flip the same bit in both arguments. (Many popular kernels have this prop...
Thorsten Doliwa, Michael Kallweit, Hans-Ulrich Sim...
TCS
2011
13 years 2 months ago
Smart PAC-learners
The PAC-learning model is distribution-independent in the sense that the learner must reach a learning goal with a limited number of labeled random examples without any prior know...
Malte Darnstädt, Hans-Ulrich Simon
STAIRS
2008
109views Education» more  STAIRS 2008»
13 years 9 months ago
Representing Case Variations for Learning General and Specific Adaptation Rules
Adaptation is a task of case-based reasoning systems that is largely domain-dependant. This motivates the study of adaptation knowledge acquisition (AKA) that can be carried out th...
Fadi Badra, Jean Lieber
FLAIRS
2008
13 years 10 months ago
Adapting Decision Trees for Learning Selectional Restrictions
This paper describes the implementation of a system that automatically learns selectional restrictions for individual senses of polysemous verbs from subject-object relationships....
Sean R. Szumlanski, Fernando Gomez