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» Approximate Learning of Dynamic Models
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NIPS
2001
15 years 6 months ago
Model-Free Least-Squares Policy Iteration
We propose a new approach to reinforcement learning which combines least squares function approximation with policy iteration. Our method is model-free and completely off policy. ...
Michail G. Lagoudakis, Ronald Parr
PAMI
2012
13 years 7 months ago
Face Recognition Using Sparse Approximated Nearest Points between Image Sets
—We propose an efficient and robust solution for image set classification. A joint representation of an image set is proposed which includes the image samples of the set and thei...
Yiqun Hu, Ajmal S. Mian, Robyn A. Owens
127
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NIPS
2003
15 years 6 months ago
Dynamical Modeling with Kernels for Nonlinear Time Series Prediction
We consider the question of predicting nonlinear time series. Kernel Dynamical Modeling (KDM), a new method based on kernels, is proposed as an extension to linear dynamical model...
Liva Ralaivola, Florence d'Alché-Buc
AAAI
2007
15 years 7 months ago
Adaptive Localization in a Dynamic WiFi Environment through Multi-view Learning
Accurately locating users in a wireless environment is an important task for many pervasive computing and AI applications, such as activity recognition. In a WiFi environment, a m...
Sinno Jialin Pan, James T. Kwok, Qiang Yang, Jeffr...
CIRA
2007
IEEE
179views Robotics» more  CIRA 2007»
15 years 11 months ago
Learning Tactic-Based Motion Models of a Moving Object with Particle Filtering
— Learning motion models of a moving object is a challenge for autonomous robots. We address the particular instance of parameter learning when tracking object motions in a switc...
Yang Gu, Manuela M. Veloso