Beata Beigman Klebanov

Artificial Intelligence · 2009

A researcher in the Science corpus: 1 paper; trusts 2 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

Whom Beata Beigman Klebanov trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

  1. Michael Collins
  2. Michael Kearns
  3. Nigel P. Duffy
  4. David Haussler
  5. Yoav Freund

Who trusts Beata Beigman Klebanov overall

  1. Jacob Goldberger
  2. Shruti Bhargava
  3. Tong Xiao
  4. Ehud Ben-Reuven
  5. David A. Forsyth

Papers from Beata Beigman Klebanov's perspective

Ordered by how strongly the researchers Beata Beigman Klebanov trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Discriminative Training Methods for Hidden Markov Models: Theory and Experiments with Perceptron Algorithms
  2. Incremental Parsing with the Perceptron Algorithm
  3. Ranking Algorithms for Named Entity Extraction: Boosting and the VotedPerceptron (Annual Meeting of the Association for Computational Linguistics)
  4. New Ranking Algorithms for Parsing and Tagging: Kernels over Discrete Structures, and the Voted Perceptron (Annual Meeting of the Association for Computational Linguistics)
  5. Large Margin Classification Using the Perceptron Algorithm
  6. Learning in the presence of malicious errors
  7. Decision Theoretic Generalizations of the PAC Model for Neural Net and Other Learning Applications
  8. Toward Efficient Agnostic Learning
  9. Cheap and Fast – But is it Good? Evaluating Non-Expert Annotations for Natural Language Tasks
  10. Learning From Noisy Examples

Their papers