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98
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IJCNN
2000
IEEE
15 years 6 months ago
An Incremental Growing Neural Network and its Application to Robot Control
This paper describes a novel network model, which is able to control its growth on the basis of the approximation requests. Two classes of self-tuning neural models are considered...
A. Carlevarino, R. Martinotti, Giorgio Metta, Giul...
84
Voted
IPPS
2008
IEEE
15 years 8 months ago
Optimal spot-checking to minimize the computation time in volunteer computing
This paper proposes an optimization technique for spotchecking to minimize the computation time of volunteer computing (VC) systems with malicious participants who return erroneou...
Kan Watanabe, Masaru Fukushi, Susumu Horiguchi
119
Voted
ENGL
2007
133views more  ENGL 2007»
15 years 1 months ago
Adaptive Wavelet-based-CMAC Network Predictor Design for Lossless Image Coding
— In this paper, we propose a novel wavelet-based-CMAC (WCMAC) network for predictive image coding. The Gaussian functions of traditional CMAC are replaced by wavelet functions. ...
Ching-Hung Lee, Bo-Hang Wang
212
Voted
CVPR
2012
IEEE
13 years 4 months ago
Finite Element based sequential Bayesian Non-Rigid Structure from Motion
Navier’s equations modelling linear elastic solid deformations are embedded within an Extended Kalman Filter (EKF) to compute a sequential Bayesian estimate for the Non-Rigid St...
Antonio Agudo, Begoña Calvo, J. M. M. Monti...
120
Voted
NIPS
1998
15 years 3 months ago
Finite-Sample Convergence Rates for Q-Learning and Indirect Algorithms
In this paper, we address two issues of long-standing interest in the reinforcement learning literature. First, what kinds of performance guarantees can be made for Q-learning aft...
Michael J. Kearns, Satinder P. Singh