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» On the Learnability of i*: Experiences from a New Teacher
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STOC
1993
ACM
117views Algorithms» more  STOC 1993»
13 years 9 months ago
Efficient noise-tolerant learning from statistical queries
In this paper, we study the problem of learning in the presence of classification noise in the probabilistic learning model of Valiant and its variants. In order to identify the cl...
Michael J. Kearns
SIGUCCS
2006
ACM
13 years 11 months ago
Better results in mathematics lessons with a virtual personal teacher
In this paper we present the results of an experiment made with our e-librarian service ”MatES”, an e-Learning tool on fractions in mathematics. MatES allows students to enter...
Serge Linckels, Carole Dording, Christoph Meinel
ROMAN
2007
IEEE
115views Robotics» more  ROMAN 2007»
13 years 12 months ago
Issues in Human/Robot Task Structuring and Teaching
—Teaching a robot new skills may require that the teacher scaffolds the teaching experience appropriately. However, due to inherent assumptions made by a human teacher the scaffo...
Joe Saunders, Nuno Otero, Chrystopher L. Nehaniv
CE
2007
102views more  CE 2007»
13 years 5 months ago
ICT and learning: Lessons from Australian classrooms
Research into Information and Communication Technologies (ICT) in schools is well into its third decade but there is still a pressing need to better understand how computer-based ...
Debra N. A. Hayes
FOCS
1990
IEEE
13 years 9 months ago
Separating Distribution-Free and Mistake-Bound Learning Models over the Boolean Domain
Two of the most commonly used models in computational learning theory are the distribution-free model in which examples are chosen from a fixed but arbitrary distribution, and the ...
Avrim Blum