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» Approximate Learning of Dynamic Models
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134
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ICML
2006
IEEE
16 years 5 months ago
Bayesian regression with input noise for high dimensional data
This paper examines high dimensional regression with noise-contaminated input and output data. Goals of such learning problems include optimal prediction with noiseless query poin...
Jo-Anne Ting, Aaron D'Souza, Stefan Schaal
AGENTS
1999
Springer
15 years 9 months ago
On Being a Teammate: Experiences Acquired in the design of RoboCup Teams
Increasingly, multi-agent systems are being designed for a variety of complex, dynamic domains. E ective agent interactions in such domains raise some of most fundamental research...
Stacy Marsella, Jafar Adibi, Yaser Al-Onaizan, Gal...
148
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OOPSLA
2005
Springer
15 years 10 months ago
GOOAL: an educational object oriented analysis laboratory
Our goal is to enable rapid production of static and dynamic object models from natural language description of problems. Rapid modeling is achieved through automation of analysis...
Hector G. Pérez-González, Jugal K. K...
AVSS
2005
IEEE
15 years 10 months ago
Multiple object tracking using elastic matching
A novel region-based multiple object tracking framework based on Kalman filtering and elastic matching is proposed. The proposed Kalman filtering-elastic matching model is gener...
Xingzhi Luo, Suchendra M. Bhandarkar
ICIAR
2005
Springer
15 years 10 months ago
A Novel Tracking Framework Using Kalman Filtering and Elastic Matching
A novel region-based multiple object tracking framework based on Kalman filtering and elastic matching is proposed. The proposed Kalman filtering-elastic matching model is genera...
Xingzhi Luo, Suchendra M. Bhandarkar