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ICDM
2009
IEEE
172views Data Mining» more  ICDM 2009»
15 years 4 months ago
Sparse Least-Squares Methods in the Parallel Machine Learning (PML) Framework
—We describe parallel methods for solving large-scale, high-dimensional, sparse least-squares problems that arise in machine learning applications such as document classificatio...
Ramesh Natarajan, Vikas Sindhwani, Shirish Tatikon...
FLAIRS
2000
14 years 11 months ago
A Parallel Approach to Modeling Language Learning and Understanding in Young Children
To reduce the complexity of studying a parallel mechanism for natural language learning and understanding which supports both utterance and discourse processing, we propose a comp...
Charles Hannon, Diane J. Cook
AAAI
2011
13 years 9 months ago
CCRank: Parallel Learning to Rank with Cooperative Coevolution
We propose CCRank, the first parallel algorithm for learning to rank, targeting simultaneous improvement in learning accuracy and efficiency. CCRank is based on cooperative coev...
Shuaiqiang Wang, Byron J. Gao, Ke Wang, Hady Wiraw...
ICPR
2008
IEEE
15 years 11 months ago
A discrete-time parallel update algorithm for distributed learning
We present a distributed machine learning framework based on support vector machines that allows classification problems to be solved iteratively through parallel update algorithm...
Christian Bauckhage, Tansu Alpcan
FCCM
2005
IEEE
124views VLSI» more  FCCM 2005»
15 years 3 months ago
Parallel Hardware Implementation of Cellular Learning Automata Based Evolutionary Computing (CLA-EC) on FPGA
The CLA-EC is a model obtained by combining the concepts of cellular learning automata and evolutionary algorithms. The parallel structure of the CLA-EC makes it suitable for hard...
Arash Hariri, Reza Rastegar, Morteza Saheb Zamani,...