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» On the Execution of Deep Models
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JMLR
2010
160views more  JMLR 2010»
13 years 1 months ago
Neural conditional random fields
We propose a non-linear graphical model for structured prediction. It combines the power of deep neural networks to extract high level features with the graphical framework of Mar...
Trinh Minh Tri Do, Thierry Artières
ICASSP
2011
IEEE
12 years 10 months ago
Deep belief nets for natural language call-routing
This paper considers application of Deep Belief Nets (DBNs) to natural language call routing. DBNs have been successfully applied to a number of tasks, including image, audio and ...
Ruhi Sarikaya, Geoffrey E. Hinton, Bhuvana Ramabha...
ICML
2009
IEEE
14 years 7 months ago
Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations
There has been much interest in unsupervised learning of hierarchical generative models such as deep belief networks. Scaling such models to full-sized, high-dimensional images re...
Honglak Lee, Roger Grosse, Rajesh Ranganath, Andre...
AGENTS
1998
Springer
13 years 11 months ago
Issues in Temporal Reasoning for Autonomous Control Systems
Deep Space One will be the rst spacecraft to be controlled by an autonomous agent potentially capable of carrying out a complete mission with minimal commandingfrom Earth. The New...
Nicola Muscettola, Paul H. Morris, Barney Pell, Be...
ASPDAC
2007
ACM
79views Hardware» more  ASPDAC 2007»
13 years 10 months ago
Challenges to Accuracy for the Design of Deep-Submicron RF-CMOS Circuits
- Two challenges for the accurate prediction of GHz CMOS analog/RF building blocks are presented. Challenging the usage of new compact MOSFET models enhances the simulation accurac...
S. Yoshitomi