Communications of the ACM
Learning regular sets from queries and counterexamples
Information and Computation
Learning from good and bad data
Learning from good and bad data
Crytographic limitations on learning Boolean formulae and finite automata
STOC '89 Proceedings of the twenty-first annual ACM symposium on Theory of computing
Learnability and the Vapnik-Chervonenkis dimension
Journal of the ACM (JACM)
Negative Results for Equivalence Queries
Machine Learning
Composite geometric concepts and polynomial predictability
COLT '90 Proceedings of the third annual workshop on Computational learning theory
Types of noise in data for concept learning
COLT '88 Proceedings of the first annual workshop on Computational learning theory
Learning k-DNF with noise in the attributes
COLT '88 Proceedings of the first annual workshop on Computational learning theory
Prediction-preserving reducibility
Journal of Computer and System Sciences - 3rd Annual Conference on Structure in Complexity Theory, June 14–17, 1988
When won't membership queries help?
STOC '91 Proceedings of the twenty-third annual ACM symposium on Theory of computing
On learning from queries and counterexamples in the presence of noise
Information Processing Letters
Redundant noisy attributes, attribute errors, and linear-threshold learning using winnow
COLT '91 Proceedings of the fourth annual workshop on Computational learning theory
Learning 2u DNF formulas and ku decision trees
COLT '91 Proceedings of the fourth annual workshop on Computational learning theory
Exact learning of read-twice DNF formulas (extended abstract)
SFCS '91 Proceedings of the 32nd annual symposium on Foundations of computer science
Equivalence of models for polynomial learnability
Information and Computation
Learning arithmetic read-once formulas
STOC '92 Proceedings of the twenty-fourth annual ACM symposium on Theory of computing
Fast learning of k-term DNF formulas with queries
STOC '92 Proceedings of the twenty-fourth annual ACM symposium on Theory of computing
Learning Boolean read-once formulas with arbitrary symmetric and constant fan-in gates
COLT '92 Proceedings of the fifth annual workshop on Computational learning theory
On-line learning of rectangles
COLT '92 Proceedings of the fifth annual workshop on Computational learning theory
Learning read-once formulas with queries
Journal of the ACM (JACM)
Learning Conjunctions of Horn Clauses
Machine Learning - Computational learning theory
Exact identification of read-once formulas using fixed points of amplification functions
SIAM Journal on Computing
Learning in the presence of malicious errors
SIAM Journal on Computing
Learning unions of two rectangles in the plane with equivalence queries
COLT '93 Proceedings of the sixth annual conference on Computational learning theory
COLT '94 Proceedings of the seventh annual conference on Computational learning theory
Learning with malicious membership queries and exceptions (extended abstract)
COLT '94 Proceedings of the seventh annual conference on Computational learning theory
Learning unions of boxes with membership and equivalence queries
COLT '94 Proceedings of the seventh annual conference on Computational learning theory
Randomly Fallible Teachers: Learning Monotone DNF with an Incomplete Membership Oracle
Machine Learning - Special issue on computational learning theory
Machine Learning
COLT '94 Proceedings of the seventh annual conference on Computational learning theory
Learning unions of boxes with membership and equivalence queries
COLT '94 Proceedings of the seventh annual conference on Computational learning theory
Learning with unreliable boundary queries
COLT '95 Proceedings of the eighth annual conference on Computational learning theory
Noise-tolerant parallel learning of geometric concepts
COLT '95 Proceedings of the eighth annual conference on Computational learning theory
Exactly learning automata with small cover time
COLT '95 Proceedings of the eighth annual conference on Computational learning theory
Noise-tolerant distribution-free learning of general geometric concepts
STOC '96 Proceedings of the twenty-eighth annual ACM symposium on Theory of computing
Exactly Learning Automata of Small Cover Time
Machine Learning - Special issue on the eighth annual conference on computational learning theory, (COLT '95)
Malicious Omissions and Errors in Answers to Membership Queries
Machine Learning
Learning from examples with unspecified attribute values (extended abstract)
COLT '97 Proceedings of the tenth annual conference on Computational learning theory
Structural results about exact learning with unspecified attribute values
COLT' 98 Proceedings of the eleventh annual conference on Computational learning theory
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One view of computational learning theory is that of a learner acquiring the knowledge of a teacher. We introduce a formal model of learning capturing the idea that teachers may have gaps in their knowledge. The goal of the learner is still to acquire the knowledge of the teacher, but now the learner must also identify the gaps. This is the notion of learning from a consistently ignorant teacher. We consider the impact of knowledge gaps on learning, for example, monotone DNF and d-dimensional boxes, and show that learning is still possible. Negatively, we show that knowledge gaps make learning conjunctions of Horn clauses as hard as learning DNF. We also present general results describing when known learning algorithms can be used to obtain learning algorithms using a consistently ignorant teacher.