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» Modeling Neural Processes in Lindenmayer Systems
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101
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ICANN
2003
Springer
15 years 5 months ago
Meta-learning for Fast Incremental Learning
Model based learning systems usually face to a problem of forgetting as a result of the incremental learning of new instances. Normally, the systems have to re-learn past instances...
Takayuki Oohira, Koichiro Yamauchi, Takashi Omori
115
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ICCS
2004
Springer
15 years 5 months ago
Developing a Data Driven System for Computational Neuroscience
Abstract. A data driven system implies the need to integrate data acquisition and signal processing into the same system that will interact with this information. This can be done ...
Ross Snider, Yongming Zhu
84
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ICASSP
2008
IEEE
15 years 6 months ago
System combination using auxiliary information for speaker verification
Recent studies in speaker recognition have shown that scorelevel combination of subsystems can yield significant performance gains over individual subsystems. We explore the use ...
Luciana Ferrer, Martin Graciarena, Argyrios Zymnis...
135
Voted
ICA
2007
Springer
15 years 6 months ago
Hierarchical ALS Algorithms for Nonnegative Matrix and 3D Tensor Factorization
In the paper we present new Alternating Least Squares (ALS) algorithms for Nonnegative Matrix Factorization (NMF) and their extensions to 3D Nonnegative Tensor Factorization (NTF) ...
Andrzej Cichocki, Rafal Zdunek, Shun-ichi Amari
125
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JIRS
2008
100views more  JIRS 2008»
15 years 11 days ago
Model-based Predictive Control of Hybrid Systems: A Probabilistic Neural-network Approach to Real-time Control
Abstract This paper proposes an approach for reducing the computational complexity of a model-predictive-control strategy for discrete-time hybrid systems with discrete inputs only...
Bostjan Potocnik, Gasper Music, Igor Skrjanc, Boru...