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» Vector instruction set support for conditional operations
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ICPR
2002
IEEE
14 years 6 months ago
Incorporating Conditional Independence Assumption with Support Vector Machines to Enhance Handwritten Character Segmentation Per
Learning Bayesian Belief Networks (BBN) from corpora and incorporating the extracted inferring knowledge with a Support Vector Machines (SVM) classifier has been applied to charac...
Manolis Maragoudakis, Ergina Kavallieratou, Nikos ...
CVBIA
2005
Springer
13 years 10 months ago
Segmenting Brain Tumors with Conditional Random Fields and Support Vector Machines
Abstract. Markov Random Fields (MRFs) are a popular and wellmotivated model for many medical image processing tasks such as segmentation. Discriminative Random Fields (DRFs), a dis...
Chi-Hoon Lee, Mark Schmidt, Albert Murtha, Aalo Bi...
AAAI
2008
13 years 7 months ago
Markov Blanket Feature Selection for Support Vector Machines
Based on Information Theory, optimal feature selection should be carried out by searching Markov blankets. In this paper, we formally analyze the current Markov blanket discovery ...
Jianqiang Shen, Lida Li, Weng-Keen Wong
IEEEPACT
1998
IEEE
13 years 9 months ago
Dynamic Hammock Predication for Non-Predicated Instruction Set Architectures
Conventional speculative architectures use branch prediction to evaluate the most likely execution path during program execution. However, certain branches are difficult to predic...
Artur Klauser, Todd M. Austin, Dirk Grunwald, Brad...
CASES
2003
ACM
13 years 10 months ago
Vectorizing for a SIMdD DSP architecture
The Single Instruction Multiple Data (SIMD) model for fine-grained parallelism was recently extended to support SIMD operations on disjoint vector elements. In this paper we demon...
Dorit Naishlos, Marina Biberstein, Shay Ben-David,...