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Full-Text Articles in Physical Sciences and Mathematics
Effective Auto Encoder For Unsupervised Sparse Representation, Faria Mahnaz
Effective Auto Encoder For Unsupervised Sparse Representation, Faria Mahnaz
Wayne State University Theses
High dimensionality and the sheer size of unlabeled data available today demand
new development in unsupervised learning of sparse representation. Despite of recent
advances in representation learning, most of the current methods are limited when
dealing with large scale unlabeled data. In this study, we propose a new unsupervised
method that is able to learn sparse representation from unlabeled data efficiently. We
derive a closed-form solution based on the sequential minimal optimization (SMO)
for training an auto encoder-decoder module, which efficiently extracts sparse and
compact features from any data set with various size. The inference process in the
proposed learning …
The Impact Of Increased Optimization Problem Dimensionality On Cultural Algorithm Performance, Yang Yang
The Impact Of Increased Optimization Problem Dimensionality On Cultural Algorithm Performance, Yang Yang
Wayne State University Theses
ABSTRACT
The Impact of Increased Optimization Problem Dimensionality on
Cultural Algorithm Performance
by
Yang Yang
August 2015
Advisor: Dr. Robert Reynolds
Major: Computer Science
Degree: Master of Science
In this thesis, we investigate the performance of Cultural Algorithms when dealing with the increasing dimensionality of optimization problems. The research is based on previous cultural algorithm approaches with the Cultural Algorithms Toolkit, CAT 2.0, which supports a variety of co-evolutionary features at both the knowledge and population levels. In this project, the system was applied to the solution of 60 randomly generated problems that ranged from 2-dimensional to 5-dimensional problem spaces. …