AbstractMost theories of learning consider inferring a function f from either (1) observations about f or, (2) questions about f. We consider a scenario whereby the learner observes f and asks queries to some set A. If I is a notion of learning then I[A] is the set of concept classes I-learnable by an inductive inference machine with oracle A. A and B are I-equivalent if I[A] = I[B]. The equivalence classes induced are the degrees of inferability. We prove several results about when these degrees are trivial, and when the degrees are omniscient (i.e., the set of recursive function is learnable)
AbstractElimination of potential hypotheses is a fundamental component of many learning processes. I...
AbstractThis paper is concerned with the algorithmic learning, by example in the limit, of programs ...
Proc. 3rd Workshop on Algorithmic Learning Theory, 125-134, 1992In this paper, we deal with inductiv...
AbstractMost theories of learning consider inferring a function f from either (1) observations about...
AbstractDegrees of inferability have been introduced to measure the learning power of inductive infe...
AbstractDegrees of inferability have been introduced to measure the learning power of inductive infe...
AbstractIn this paper we survey some results in inductive inference showing how learnability of a cl...
This paper provides a systematic study of inductive inference of indexable concept classes in learni...
AbstractIn this paper we study the question of whether identifiable classes have subclasses which ar...
Intuitively, a class of objects is robustly learnable if not only this class itself is learnable but...
We study the learnability of indexed families L = (L j ) j2IN of uniformly recursive languages under...
We study the learnability of indexed families of uniformly recursive languages under certain monoton...
AbstractIntuitively, a class of objects is robustly learnable if not only this class itself is learn...
Ph.D. ThesisInductive inference is a process of hypothesizing a general rule from examples. As a suc...
AbstractA class of computable functions ismaximaliff it can be incrementally learned by some inducti...
AbstractElimination of potential hypotheses is a fundamental component of many learning processes. I...
AbstractThis paper is concerned with the algorithmic learning, by example in the limit, of programs ...
Proc. 3rd Workshop on Algorithmic Learning Theory, 125-134, 1992In this paper, we deal with inductiv...
AbstractMost theories of learning consider inferring a function f from either (1) observations about...
AbstractDegrees of inferability have been introduced to measure the learning power of inductive infe...
AbstractDegrees of inferability have been introduced to measure the learning power of inductive infe...
AbstractIn this paper we survey some results in inductive inference showing how learnability of a cl...
This paper provides a systematic study of inductive inference of indexable concept classes in learni...
AbstractIn this paper we study the question of whether identifiable classes have subclasses which ar...
Intuitively, a class of objects is robustly learnable if not only this class itself is learnable but...
We study the learnability of indexed families L = (L j ) j2IN of uniformly recursive languages under...
We study the learnability of indexed families of uniformly recursive languages under certain monoton...
AbstractIntuitively, a class of objects is robustly learnable if not only this class itself is learn...
Ph.D. ThesisInductive inference is a process of hypothesizing a general rule from examples. As a suc...
AbstractA class of computable functions ismaximaliff it can be incrementally learned by some inducti...
AbstractElimination of potential hypotheses is a fundamental component of many learning processes. I...
AbstractThis paper is concerned with the algorithmic learning, by example in the limit, of programs ...
Proc. 3rd Workshop on Algorithmic Learning Theory, 125-134, 1992In this paper, we deal with inductiv...