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NIPS
2007
15 years 7 months ago
Transfer Learning using Kolmogorov Complexity: Basic Theory and Empirical Evaluations
In transfer learning we aim to solve new problems using fewer examples using information gained from solving related problems. Transfer learning has been successful in practice, a...
M. M. Mahmud, Sylvian R. Ray
JODL
2007
126views more  JODL 2007»
15 years 6 months ago
Building rich, semantic descriptions of learning activities to facilitate reuse in digital libraries
Abstract This paper describes efforts to extend educational descriptions of learning objects to enable semantic search for suitable resources held within digital libraries and cybe...
Mark Gahegan, Ritesh Agrawal, Tawan Banchuen, Davi...
IROS
2006
IEEE
168views Robotics» more  IROS 2006»
16 years 9 days ago
Learning to Drive Among Obstacles
— This paper reports on an outdoor mobile robot that learns to avoid collisions by observing a human driver operate a vehicle equipped with sensors that continuously produce a ma...
Bradley Hamner, Sebastian Scherer, Sanjiv Singh
ICDM
2002
IEEE
133views Data Mining» more  ICDM 2002»
15 years 11 months ago
Learning with Progressive Transductive Support Vector Machine
Support vector machine (SVM) is a new learning method developed in recent years based on the foundations of statistical learning theory. By taking a transductive approach instead ...
Yisong Chen, Guoping Wang, Shihai Dong
ALT
1998
Springer
15 years 10 months ago
Predictive Learning Models for Concept Drift
Concept drift means that the concept about which data is obtained may shift from time to time, each time after some minimum permanence. Except for this minimum permanence, the con...
John Case, Sanjay Jain, Susanne Kaufmann, Arun Sha...