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» Convex Factorization Machines
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109
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LREC
2010
181views Education» more  LREC 2010»
15 years 2 months ago
Linguistically Motivated Unsupervised Segmentation for Machine Translation
In this paper we use statistical machine translation and morphology information from two different morphological analyzers to try to improve translation quality by linguistically ...
Mark Fishel, Harri Kirik
88
Voted
ICMLA
2008
15 years 2 months ago
Ensemble Machine Methods for DNA Binding
We introduce three ensemble machine learning methods for analysis of biological DNA binding by transcription factors (TFs). The goal is to identify both TF target genes and their ...
Yue Fan, Mark A. Kon, Charles DeLisi
112
Voted
ICML
2010
IEEE
15 years 1 months ago
Restricted Boltzmann Machines are Hard to Approximately Evaluate or Simulate
Restricted Boltzmann Machines (RBMs) are a type of probability model over the Boolean cube {-1, 1}n that have recently received much attention. We establish the intractability of ...
Philip M. Long, Rocco A. Servedio
NECO
2008
170views more  NECO 2008»
15 years 16 days ago
Representational Power of Restricted Boltzmann Machines and Deep Belief Networks
Deep Belief Networks (DBN) are generative neural network models with many layers of hidden explanatory factors, recently introduced by Hinton et al., along with a greedy layer-wis...
Nicolas Le Roux, Yoshua Bengio
126
Voted
SIGIR
2004
ACM
15 years 6 months ago
Human versus machine in the topic distillation task
This paper reports on and discusses a set of user experiments using the TREC 2003 Web interactive track protocol. The focus is on comparing humans and machine algorithms in terms ...
Mingfang Wu, Gheorghe Muresan, Alistair McLean, Mu...