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» On the Execution of Deep Models
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MBEC
2011
198views more  MBEC 2011»
13 years 2 months ago
Clinically oriented real-time monitoring of the individual's risk for deep tissue injury
Spinal cord injury patients are under daily risk for developing deep tissue injury which is a severe pressure ulcer that initiates in soft tissues at the bones’ proximity. We aim...
Sigal Portnoy, Nicolas Vuillerme, Yohan Payan, Ami...
ICDE
2012
IEEE
269views Database» more  ICDE 2012»
11 years 9 months ago
A Deep Embedding of Queries into Ruby
—We demonstrate SWITCH, a deep embedding of relational queries into RUBY and RUBY on RAILS. With SWITCH, there is no syntactic or stylistic difference between RUBY programs that ...
Torsten Grust, Manuel Mayr
JMLR
2010
106views more  JMLR 2010»
13 years 2 months ago
Why Does Unsupervised Pre-training Help Deep Learning?
Much recent research has been devoted to learning algorithms for deep architectures such as Deep Belief Networks and stacks of auto-encoder variants, with impressive results obtai...
Dumitru Erhan, Yoshua Bengio, Aaron C. Courville, ...
ISCAS
2002
IEEE
65views Hardware» more  ISCAS 2002»
14 years 7 days ago
Maximum achievable energy reduction using coding with applications to deep sub-micron buses
: In this work, the problem of the computation of the minimum energy per bit required for communicating through deep sub-micron buses at a given bit rate is solved with an explicit...
Paul-Peter Sotiriadis, Anantha Chandrakasan, Vahid...
PATMOS
2004
Springer
14 years 20 days ago
Leakage Power Analysis and Comparison of Deep Submicron Logic Gates
Basic combinational gates, including NAND, NOR and XOR, are fundamental building blocks in CMOS digital circuits. This paper analyses and compares the power consumption due to tran...
Geoff V. Merrett, Bashir M. Al-Hashimi