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» Dynamic power management using machine learning
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FPCA
1995
15 years 7 months ago
How Much Non-Strictness do Lenient Programs Require?
Lenient languages, such as Id90, have been touted as among the best functional languages for massively parallel machines AHN88]. Lenient evaluation combines non-strict semantics w...
Klaus E. Schauser, Seth Copen Goldstein
KDD
2006
ACM
179views Data Mining» more  KDD 2006»
16 years 4 months ago
Extracting key-substring-group features for text classification
In many text classification applications, it is appealing to take every document as a string of characters rather than a bag of words. Previous research studies in this area mostl...
Dell Zhang, Wee Sun Lee
162
Voted
ICCV
2011
IEEE
14 years 4 months ago
The NBNN kernel
Naive Bayes Nearest Neighbor (NBNN) has recently been proposed as a powerful, non-parametric approach for object classification, that manages to achieve remarkably good results t...
Tinne Tuytelaars, Mario Fritz, Kate Saenko, Trevor...
DATE
2007
IEEE
148views Hardware» more  DATE 2007»
15 years 10 months ago
Temperature aware task scheduling in MPSoCs
In deep submicron circuits, elevation in temperatures has brought new challenges in reliability, timing, performance, cooling costs and leakage power. Conventional thermal managem...
Ayse Kivilcim Coskun, Tajana Simunic Rosing, Keith...
ICML
2006
IEEE
16 years 4 months ago
Online decoding of Markov models under latency constraints
The Viterbi algorithm is an efficient and optimal method for decoding linear-chain Markov Models. However, the entire input sequence must be observed before the labels for any tim...
Mukund Narasimhan, Paul A. Viola, Michael Shilman