Machine Learning（ML ）的AUGUST 1990, ISSUE 3论文列表

卷期号： August 1990, issue 3

发布时间：

卷期年份： 1990

卷期官网： https://link.springer.com/journal/10994/volumes-and-issues/5-3

Editorial advice to Machine Learning authors

Editorial: Advice to Machine Learning Authors

Learning logical definitions from relations

Learning Logical Definitions from Relations

Empirical Learning as a Function of Concept Character

Empirical learning as a function of concept character

The problem of expensive chunks and its solution by restricting expressiveness

The Problem of Expensive Chunks and its Solution by Restricting Expressiveness

Introduction: Special issue on computational learning theory

Introduction: Special Issue on Computational Learning Theory

Negative Results for Equivalence Queries

Negative results for equivalence queries

Polynomial time learnability of simple deterministic languages

Polynomial Time Learnability of Simple Deterministic Languages

Learning Nested Differences of Intersection-Closed Concept Classes

Learning nested differences of intersection-closed concept classes

The strength of weak learnability

The Strength of Weak Learnability

Errata

Editorial

Editorial Exploratory research in machine learning

Extending domain theories: Two case studies in student modeling

Extending Domain Theories: Two Case Studies in Student Modeling

Acquiring Recursive and Iterative Concepts with Explanation-Based Learning

Acquiring recursive and iterative concepts with explanation-based learning

Boolean Feature Discovery in Empirical Learning

Boolean feature discovery in empirical learning

A necessary condition for learning from positive examples

A Necessary Condition for Learning from Positive Examples

Announcements

Introduction

Learning Sequential Decision Rules Using Simulation Models and Competition

Learning sequential decision rules using simulation models and competition

CSM: A Computational Model of Cumulative Learning

CSM: A computational model of cumulative learning

Probability Matching, the Magnitude of Reinforcement, and Classifier System Bidding

Probability matching, the magnitude of reinforcement, and classifier system bidding

Empirical learning using rule threshold optimization for detection of events in synthetic images

Empirical Learning Using Rule Threshold Optimization for Detection of Events in Synthetic Images

Call for papers for ICGA-91