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» Hierarchical Text Categorization Using Neural Networks
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IEEEPACT
2008
IEEE
14 years 2 months ago
Feature selection and policy optimization for distributed instruction placement using reinforcement learning
Communication overheads are one of the fundamental challenges in a multiprocessor system. As the number of processors on a chip increases, communication overheads and the distribu...
Katherine E. Coons, Behnam Robatmili, Matthew E. T...
IDA
1998
Springer
13 years 7 months ago
Self-Organized-Expert Modular Network for Classification of Spatiotemporal Sequences
We investigate a form of modular neural network for classification with (a) pre-separated input vectors entering its specialist (expert) networks, (b) specialist networks which ar...
Sylvian R. Ray, William H. Hsu
ISNN
2011
Springer
12 years 10 months ago
Orthogonal Feature Learning for Time Series Clustering
This paper presents a new method that uses orthogonalized features for time series clustering and classification. To cluster or classify time series data, either original data or...
Xiaozhe Wang, Leo Lopes
NIPS
1990
13 years 8 months ago
Bumptrees for Efficient Function, Constraint and Classification Learning
A new class of data structures called "bumptrees" is described. These structures are useful for efficiently implementing a number of neural network related operations. A...
Stephen M. Omohundro
BMCBI
2008
147views more  BMCBI 2008»
13 years 7 months ago
Transmembrane helix prediction using amino acid property features and latent semantic analysis
Background: Prediction of transmembrane (TM) helices by statistical methods suffers from lack of sufficient training data. Current best methods use hundreds or even thousands of f...
Madhavi Ganapathiraju, Narayanas Balakrishnan, Raj...