B. K´egl
Artificial Intelligence · 2012
A researcher in the Science corpus: 1 paper; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 5 citations into it
- Information Retrieval & Search — 5 citations into it
Whom B. K´egl trusts
Their strongest outbound trust, strongest first, inferred from their citations.
- Hang Li (in Artificial Intelligence)
- Jun Xu (in Artificial Intelligence)
- Stephen E. Robertson (in Information Retrieval & Search)
- Hugo Zaragoza (in Artificial Intelligence)
Papers from B. K´egl's perspective
Ordered by how strongly the researchers B. K´egl trusts endorse each paper. Same corpus, a different order for every researcher.
- Learning to rank using gradient descent
- AdaRank: a boosting algorithm for information retrieval (Annual International ACM SIGIR Conference on Research and Development in Information Retrieval)
- Large margin rank boundaries for ordinal regression
- The Probabilistic Relevance Framework: BM25 and Beyond
- Linear feature-based models for information retrieval
- Statistical Analysis of Bayes Optimal Subset Ranking
- IR evaluation methods for retrieving highly relevant documents
- The Anatomy of a Large-Scale Hypertextual Web Search Engine
- Authoritative sources in a hyperlinked environment
- Learning to Rank with Nonsmooth Cost Functions