Inductive Inference

Probabilistic inductive inference: a survey

Inductive inference is a recursion-theoretic theory of learning, rst developed by E. M. Gold (1967). This paper surveys developments in probabilistic inductive inference. We mainly focus on nite inference of recursive functions, since this simple paradigm has produced the most interesting (and most complex) results.

Inference to the Best Inductive Practices

a SPECIAL ISSUE III, pp. 18 – 26, 2009 INFERENCE TO THE BEST INDUCTIVE PRACTICES

Is Holism A Problem For Inductive Inference? A Computational Analysis

We investigate whether holism presents a problem for inductive inference by examining the relationship between the size of a Bayesian network that represents human conceptual knowledge and the computational complexity of probabilistic inference in that network. We find that, despite prior claims, holism may not be a problem for inductive inference, as computational cost does not increase expone...

(yip-10) Fast, Flexible, Rational Inductive Inference

Inductive Inference of Real Functions

Inductive Inference by Using Information Compression

Inductive inference is of central importance to all scientific inquiries. Automating the process of inductive inference is the major concern of machine learning researchers. This article proposes inductive inference techniques to address three inductive problems: (1) how to automatically construct a general description, a model, or a theory to describe a sequence of observations or experimental...