Philip D. Laird
1988
A researcher in the Science corpus: 1 paper; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.
Whom Philip D. Laird trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
Who trusts Philip D. Laird overall
- Vitaly Feldman
- Zhi-Hua Zhou
- Ming Li
- Valter Crescenzi
- François Denis
- Michael P. O'Mahony
- Curtis G. Northcutt
Papers from Philip D. Laird's perspective
Ordered by how strongly the researchers Philip D. Laird trusts endorse each paper. Same corpus, a different order for every researcher.
- Learning Regular Sets from Queries and Counterexamples
- On the learnability of Boolean formulae
- A theory of the learnable
- Learning Disjunction of Conjunctions
- Chervonenkis: On the uniform convergence of relative frequencies of events to their probabilities
- Occam's Razor
- A theory of the learnable
- Learning Quickly When Irrelevant Attributes Abound: A New Linear-Threshold Algorithm
- The complexity of theorem-proving procedures
- A logical calculus of the ideas immanent in nervous activity
Their papers
- Learning From Noisy Examples (1988)