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ORCIDMachine Learning, Volume 21, 1995
Volume 21, Numbers 1-2, 1995
- Jude W. Shavlik, Lawrence Hunter
, David B. Searls:
Introduction. 5-9 - Rebecca J. Parsons, Stephanie Forrest, Christian Burks:
Genetic Algorithms, Operators, and DNA Fragment Assembly. 11-33 - Aleksandar Milosavljevic:
Discovering Dependencies via Algorithmic Mutual Information: A Case Study in DNA Sequence Comparisons. 35-50 - Timothy L. Bailey, Charles Elkan:
Unsupervised Learning of Multiple Motifs in Biopolymers Using Expectation Maximization. 51-80 - Dawn M. Cohen, Casimir A. Kulikowski, Helen Berman:
Dexter: A System that Experiments with Choices of Training Data Using Expert Knowledge in the Domain of DNA Hydration. 81-101 - Alan S. Lapedes, Evan W. Steeg, Robert M. Farber:
Use of Adaptive Networks to Define Highly Predictable Protein Secondary-Structure Classes. 103-124 - Darrell Conklin:
Machine Discovery of Protein Motifs. 125-150 - Thomas R. Ioerger, Larry A. Rendell, Shankar Subramaniam:
Searching for Representations to Improve Protein Sequence Fold-Class Prediction. 151-175 - Cathy H. Wu, Michael W. Berry, Sailaja Shivakumar:
Neural Networks for Full-Scale Protein Sequence Classification: Sequence Encoding with Singular Value Decomposition. 177-193
Volume 21, Number 3, 1995
- Andrew W. Moore, Christopher G. Atkeson:
The Parti-game Algorithm for Variable Resolution Reinforcement Learning in Multidimensional State-spaces. 199-233 - Jianping Zhang, Ryszard S. Michalski:
An Integration of Rule Induction and Exemplar-Based Learning for Graded Concepts. 235-267 - Sally Floyd, Manfred K. Warmuth:
Sample Compression, Learnability, and the Vapnik-Chervonenkis Dimension. 269-304
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