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PR
2008
154views more  PR 2008»
13 years 5 months ago
Data-driven decomposition for multi-class classification
This paper presents a new study on a method of designing a multi-class classifier: Data-driven Error Correcting Output Coding (DECOC). DECOC is based on the principle of Error Cor...
Jie Zhou, Hanchuan Peng, Ching Y. Suen
CP
2009
Springer
14 years 2 days ago
Exploiting Problem Decomposition in Multi-objective Constraint Optimization
Multi-objective optimization is concerned with problems involving multiple measures of performance which should be optimized simultaneously. In this paper, we extend AND/OR Branch-...
Radu Marinescu
VLSISP
2011
358views Database» more  VLSISP 2011»
13 years 6 days ago
Accelerating Machine-Learning Algorithms on FPGAs using Pattern-Based Decomposition
Machine-learning algorithms are employed in a wide variety of applications to extract useful information from data sets, and many are known to suffer from superlinear increases in ...
Karthik Nagarajan, Brian Holland, Alan D. George, ...
FLAIRS
2004
13 years 6 months ago
Transductive LSI for Short Text Classification Problems
This paper presents work that uses Transductive Latent Semantic Indexing (LSI) for text classification. In addition to relying on labeled training data, we improve classification ...
Sarah Zelikovitz
NPL
2006
90views more  NPL 2006»
13 years 5 months ago
Hierarchical Incremental Class Learning with Reduced Pattern Training
Hierarchical Incremental Class Learning (HICL) is a new task decomposition method that addresses the pattern classification problem. HICL is proven to be a good classifier but clos...
Sheng Uei Guan, Chunyu Bao, Ru-Tian Sun