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» Using and Combining Predictors That Specialize
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BMCBI
2006
132views more  BMCBI 2006»
13 years 7 months ago
Length-dependent prediction of protein intrinsic disorder
Background: Due to the functional importance of intrinsically disordered proteins or protein regions, prediction of intrinsic protein disorder from amino acid sequence has become ...
Kang Peng, Predrag Radivojac, Slobodan Vucetic, A....
KDD
2002
ACM
179views Data Mining» more  KDD 2002»
14 years 7 months ago
Combining clustering and co-training to enhance text classification using unlabelled data
In this paper, we present a new co-training strategy that makes use of unlabelled data. It trains two predictors in parallel, with each predictor labelling the unlabelled data for...
Bhavani Raskutti, Herman L. Ferrá, Adam Kow...
MICRO
1999
IEEE
123views Hardware» more  MICRO 1999»
13 years 11 months ago
Improving Branch Predictors by Correlating on Data Values
Branch predictors typically use combinations of branch PC bits and branch histories to make predictions. Recent improvements in branch predictors have come from reducing the effec...
Timothy H. Heil, Zak Smith, James E. Smith
MICRO
1999
IEEE
131views Hardware» more  MICRO 1999»
13 years 11 months ago
Value Prediction for Speculative Multithreaded Architectures
The speculative multithreading paradigm (speculative threadlevel parallelism) is based on the concurrent execution of control-speculative threads. The efficiency of microarchitect...
Pedro Marcuello, Jordi Tubella, Antonio Gonz&aacut...
ICCD
2000
IEEE
75views Hardware» more  ICCD 2000»
14 years 4 months ago
Hybridizing and Coalescing Load Value Predictors
Most well-performing load value predictors are hybrids that combine multiple predictors into one. Such hybrids are often large. To reduce their size and to improve their performan...
Martin Burtscher, Benjamin G. Zorn