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RECOMB
2008
Springer
15 years 9 months ago
Automatic Parameter Learning for Multiple Network Alignment
We developed Gr?mlin 2.0, a new multiple network aligner with (1) a novel scoring function that can use arbitrary features of a multiple network alignment, such as protein deletion...
Jason Flannick, Antal F. Novak, Chuong B. Do, Bala...
ICASSP
2011
IEEE
14 years 1 months ago
Defining the controlling parameter in constrained discriminative linear transform for supervised speaker adaptation
Constrained discriminative linear transform (CDLT) optimized with Extended Baum-Welch (EBW) has been presented in the literature as a discriminative speaker adaptation method that...
Danning Jiang, Dimitri Kanevsky, Emmanuel Yashchin...
ESANN
2003
14 years 10 months ago
Autonomous learning algorithm for fully connected recurrent networks
In this paper fully connected RTRL neural networks are studied. In order to learn dynamical behaviours of linear-processes or to predict time series, an autonomous learning algori...
Edouard Leclercq, Fabrice Druaux, Dimitri Lefebvre
ESANN
2007
14 years 11 months ago
Intrinsic plasticity for reservoir learning algorithms
One of the most difficult problems in using dynamic reservoirs like echo state networks for signal processing is the choice of reservoir network parameters like connectivity or spe...
Marion Wardermann, Jochen J. Steil
WSDM
2012
ACM
259views Data Mining» more  WSDM 2012»
13 years 5 months ago
Learning recommender systems with adaptive regularization
Many factorization models like matrix or tensor factorization have been proposed for the important application of recommender systems. The success of such factorization models dep...
Steffen Rendle