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ALT
2006
Springer
15 years 6 months ago
Learning Linearly Separable Languages
This paper presents a novel paradigm for learning languages that consists of mapping strings to an appropriate high-dimensional feature space and learning a separating hyperplane i...
Leonid Kontorovich, Corinna Cortes, Mehryar Mohri
KDD
2006
ACM
179views Data Mining» more  KDD 2006»
15 years 10 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
ICMLC
2010
Springer
14 years 7 months ago
A comparative study on two large-scale hierarchical text classification tasks' solutions
: Patent classification is a large scale hierarchical text classification (LSHTC) task. Though comprehensive comparisons, either learning algorithms or feature selection strategies...
Jian Zhang, Hai Zhao, Bao-Liang Lu
ASPLOS
2010
ACM
15 years 4 months ago
Request behavior variations
A large number of user requests execute (often concurrently) within a server system. A single request may exhibit fluctuating hardware characteristics (such as instruction comple...
Kai Shen
NN
2002
Springer
115views Neural Networks» more  NN 2002»
14 years 9 months ago
A self-organising network that grows when required
The ability to grow extra nodes is a potentially useful facility for a self-organising neural network. A network that can add nodes into its map space can approximate the input sp...
Stephen Marsland, Jonathan Shapiro, Ulrich Nehmzow