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Matrix regularization

Known as: Regularization 
In the field of statistical learning theory, matrix regularization generalizes notions of vector regularization to cases where the object to be… Expand
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Papers overview

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Highly Cited
2014
Highly Cited
2014
We present a simple regularization technique for Recurrent Neural Networks (RNNs) with Long Short-Term Memory (LSTM) units… Expand
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Highly Cited
2013
Highly Cited
2013
We introduce DropConnect, a generalization of Dropout (Hinton et al., 2012), for regularizing large fully-connected layers within… Expand
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Highly Cited
2011
Highly Cited
2011
Although Recommender Systems have been comprehensively analyzed in the past decade, the study of social-based recommender systems… Expand
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Highly Cited
2006
Highly Cited
2006
In recent years there has been a growing interest in the study of sparse representation of signals. Using an overcomplete… Expand
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Highly Cited
2005
Highly Cited
2005
Recent theoretical results describing the sum capacity when using multiple antennas to communicate with multiple users in a known… Expand
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Highly Cited
2005
Highly Cited
2005
In recent years there has been a growing interest in the study of sparse representation of signals. Using an overcomplete… Expand
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Highly Cited
2005
Highly Cited
2003
Highly Cited
2003
We present a new part-of-speech tagger that demonstrates the following ideas: (i) explicit use of both preceding and following… Expand
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Highly Cited
2002
Highly Cited
2002
DNA micro-arrays now permit scientists to screen thousands of genes simultaneously and determine whether those genes are active… Expand
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Highly Cited
1999
Highly Cited
1999
Discretizations of inverse problems lead to systems of linear equations with a highly ill-conditioned coefficient matrix, and in… Expand
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