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ICML
2005
IEEE
16 years 1 months ago
Exploration and apprenticeship learning in reinforcement learning
We consider reinforcement learning in systems with unknown dynamics. Algorithms such as E3 (Kearns and Singh, 2002) learn near-optimal policies by using "exploration policies...
Pieter Abbeel, Andrew Y. Ng
94
Voted
CVPR
2010
IEEE
15 years 5 months ago
An Online Approach: Learning-Semantic-Scene-by-Tracking and Tracking-by-Learning-Semantic-Scene
Learning the knowledge of scene structure and tracking a large number of targets are both active topics of computer vision in recent years, which plays a crucial role in surveilla...
Xuan Song, Xiaowei Shao, Huijing Zhao, Jinshi Cui,...
78
Voted
KDD
1995
ACM
148views Data Mining» more  KDD 1995»
15 years 4 months ago
Learning Arbiter and Combiner Trees from Partitioned Data for Scaling Machine Learning
Knowledge discovery in databases has become an increasingly important research topic with the advent of wide area network computing. One of the crucial problems we study in this p...
Philip K. Chan, Salvatore J. Stolfo
127
Voted
ICWL
2004
Springer
15 years 5 months ago
The Agile Teaching/Learning Methodology and Its e-Learning Platform
Abstract. The Agile Teaching/Learning Methodology (ATLM) is a teaching/learning methodology designed for higher-education based on the best practices and ideas from the field of so...
Andy Hon Wai Chun
COLT
1992
Springer
15 years 4 months ago
Learning Switching Concepts
We consider learning in situations where the function used to classify examples may switch back and forth between a small number of different concepts during the course of learnin...
Avrim Blum, Prasad Chalasani