The notion of the complexity of performing an inductive inference is defined. Some examples of the tradeoffs between the complexity of performing an inference and the accuracy of the inferred result are presented. An axiomatization of the notion of the complexity of inductive inference is developed and several results are presented which both resemble and contrast with results obtainable for the axiomatic computational complexity of recursive functions
Induction is a prevalent cognitive method in science while inductive computations are popular in ma...
Inductive learning aims at finding general rules that hold true in a database. Targeted learning see...
Inductive learning aims at finding general rules that hold true in a database. Targeted learning see...
This survey includes principal results on complexity of inductive inference for recursively enumera...
Darbā sniegts induktīvāis izvedums un tās sarežģītības apraksts. Sniegtas galvenās teorētiskās defin...
We present a critical review of descriptive complexity approaches to inductive inference. Inductive ...
AbstractThis paper is concerned with the algorithmic learning, by example in the limit, of programs ...
AbstractA natural ωpLω+1 hierarchy of successively more general criteria of success for inductive in...
AbstractThe main goal of this paper is to compare recursive algorithms such as Turing machines with ...
In this paper we investigate inductive inference identification criteria which permit infinitely man...
The main goal of this paper is to compare recursive algorithms such as Turing machines with such sup...
AbstractThis paper surveys developments in probabilistic inductive inference (learning) of recursive...
Inductive inference machines are algorithmic devices which attempt to synthesize (in the limit) prog...
AbstractReasoning to obtain the “truth” about reality, from external data, is an important, controve...
AbstractThree kinds of restrictions on inductive inference machines (IIMs) are considered: postdicti...
Induction is a prevalent cognitive method in science while inductive computations are popular in ma...
Inductive learning aims at finding general rules that hold true in a database. Targeted learning see...
Inductive learning aims at finding general rules that hold true in a database. Targeted learning see...
This survey includes principal results on complexity of inductive inference for recursively enumera...
Darbā sniegts induktīvāis izvedums un tās sarežģītības apraksts. Sniegtas galvenās teorētiskās defin...
We present a critical review of descriptive complexity approaches to inductive inference. Inductive ...
AbstractThis paper is concerned with the algorithmic learning, by example in the limit, of programs ...
AbstractA natural ωpLω+1 hierarchy of successively more general criteria of success for inductive in...
AbstractThe main goal of this paper is to compare recursive algorithms such as Turing machines with ...
In this paper we investigate inductive inference identification criteria which permit infinitely man...
The main goal of this paper is to compare recursive algorithms such as Turing machines with such sup...
AbstractThis paper surveys developments in probabilistic inductive inference (learning) of recursive...
Inductive inference machines are algorithmic devices which attempt to synthesize (in the limit) prog...
AbstractReasoning to obtain the “truth” about reality, from external data, is an important, controve...
AbstractThree kinds of restrictions on inductive inference machines (IIMs) are considered: postdicti...
Induction is a prevalent cognitive method in science while inductive computations are popular in ma...
Inductive learning aims at finding general rules that hold true in a database. Targeted learning see...
Inductive learning aims at finding general rules that hold true in a database. Targeted learning see...