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Machine Learning （ML） - December 1995, issue 3 论文列表

点击这里查看 Machine Learning 的JCR分区、影响因子等信息
卷期号： December 1995, issue 3
发布时间：
卷期年份： 1995
卷期官网： https://link.springer.com/journal/10994/volumes-and-issues/21-3
本期论文列表
The Parti-game Algorithm for Variable Resolution Reinforcement Learning in Multidimensional State-spaces

The parti-game algorithm for variable resolution reinforcement learning in multidimensional state-spaces

An Integration of Rule Induction and Exemplar-Based Learning for Graded Concepts

An integration of rule induction and exemplar-based learning for graded concepts

Sample Compression, Learnability, and the Vapnik-Chervonenkis Dimension

Sample compression, learnability, and the Vapnik-Chervonenkis dimension

Introduction

Introduction

Genetic Algorithms, Operators, and DNA Fragment Assembly

Genetic algorithms, operators, and DNA fragment assembly

Discovering Dependencies via Algorithmic Mutual Information: A Case Study in DNA Sequence Comparisons

Discovering dependencies via algorithmic mutual information: A case study in DNA sequence comparisons

Unsupervised learning of multiple motifs in biopolymers using expectation maximization

Unsupervised Learning of Multiple Motifs in Biopolymers Using Expectation Maximization

DEXTER: A system that experiments with choices of training data using expert knowledge in the domain of DNA hydration

DEXTER: A System that Experiments with Choices of Training Data Using Expert Knowledge in the Domain of DNA Hydration

Use of adaptive networks to define highly predictable protein secondary-structure classes

Use of Adaptive Networks to Define Highly Predictable Protein Secondary–Structure Classes

Machine discovery of protein motifs

Machine Discovery of Protein Motifs

Searching for Representations to Improve Protein Sequence Fold-Class Prediction

Searching for representations to improve protein sequence fold-class prediction

Neural networks for full-scale protein sequence classification: Sequence encoding with singular value decomposition

Neural Networks for Full-Scale Protein Sequence Classification: Sequence Encoding with Singular Value Decomposition