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NECO
2007
115views more  NECO 2007»
13 years 8 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...
ICCV
2003
IEEE
14 years 10 months ago
How To Deal with Point Correspondences and Tangential Velocities in the Level Set Framework
In this paper, we overcome a major drawback of the level set framework: the lack of point correspondences. We maintain explicit backward correspondences from the evolving interfac...
Jean-Philippe Pons, Gerardo Hermosillo, Renaud Ker...
ICASSP
2009
IEEE
14 years 3 months ago
Sparse LMS for system identification
We propose a new approach to adaptive system identification when the system model is sparse. The approach applies the ℓ1 relaxation, common in compressive sensing, to improve t...
Yilun Chen, Yuantao Gu, Alfred O. Hero III
CEC
2005
IEEE
14 years 2 months ago
A study on polynomial regression and Gaussian process global surrogate model in hierarchical surrogate-assisted evolutionary alg
This paper presents a study on Hierarchical Surrogate-Assisted Evolutionary Algorithm (HSAEA) using different global surrogate models for solving computationally expensive optimiza...
Zongzhao Zhou, Yew-Soon Ong, My Hanh Nguyen, Dudy ...
EDBTW
2004
Springer
14 years 2 months ago
Clustering Structured Web Sources: A Schema-Based, Model-Differentiation Approach
Abstract. The Web has been rapidly “deepened” with the prevalence of databases online. On this “deep Web,” numerous sources are structured, providing schema-rich data– Th...
Bin He, Tao Tao, Kevin Chen-Chuan Chang