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» Nonlinear Vector Resilient Functions
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CVPR
2009
IEEE
16 years 4 months ago
Learning Invariant Features Through Topographic Filter Maps
Several recently-proposed architectures for highperformance object recognition are composed of two main stages: a feature extraction stage that extracts locallyinvariant feature...
Koray Kavukcuoglu, Marc'Aurelio Ranzato, Rob Fergu...
HYBRID
2004
Springer
15 years 2 months ago
Understanding the Bacterial Stringent Response Using Reachability Analysis of Hybrid Systems
Abstract. In this paper we model coupled genetic and metabolic networks as hybrid systems. The vector fields are multi - affine, i.e., have only product - type nonlinearities to a...
Calin Belta, Peter Finin, Luc C. G. J. M. Habets, ...
CORR
2010
Springer
168views Education» more  CORR 2010»
14 years 9 months ago
Penalty Decomposition Methods for Rank Minimization
In this paper we consider general rank minimization problems with rank appearing in either objective function or constraint. We first show that a class of matrix optimization prob...
Zhaosong Lu, Yong Zhang
NECO
2007
115views more  NECO 2007»
14 years 9 months ago
Training Recurrent Networks by Evolino
In recent years, gradient-based LSTM recurrent neural networks (RNNs) solved many previously RNN-unlearnable tasks. Sometimes, however, gradient information is of little use for t...
Jürgen Schmidhuber, Daan Wierstra, Matteo Gag...
TSMC
2010
14 years 4 months ago
Probability Density Estimation With Tunable Kernels Using Orthogonal Forward Regression
A generalized or tunable-kernel model is proposed for probability density function estimation based on an orthogonal forward regression procedure. Each stage of the density estimat...
Sheng Chen, Xia Hong, Chris J. Harris