Francisco Cantú
Artificial Intelligence · 2011
A researcher in the Science corpus: 1 paper; trusts 5 researchers and is trusted by 8 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 8 citations into it
- Statistics and Probability — 6 citations into it; #6,518 of 12,932 by trust here, #10,275 by citations
- Information Systems — 5 citations into it
Whom Francisco Cantú trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Trevor J. Hastie
- Lawrence M. Leemis
- Jerome H. Friedman
- Alexandra Scacco
- Harry Zhang
- Irina Rish
- Robert Tibshirani
- Lei Yu
Who trusts Francisco Cantú overall
- J. Montgomery
- Maria De-Arteaga
- Santiago Olivella
- William Herlands
- Jason Poulos
- Joshua D. Potter
- Daniel B. Neill
Papers from Francisco Cantú's perspective
Ordered by how strongly the researchers Francisco Cantú trusts endorse each paper. Same corpus, a different order for every researcher.
- The Elements of Statistical Learning: Data Mining, Inference, and Prediction
- Tackling the Poor Assumptions of Naive Bayes Text Classifiers (International Conference on Machine Learning)
- Efficient Feature Selection via Analysis of Relevance and Redundancy (Journal of machine learning research)
- The Optimality of Naive Bayes (The Florida AI Research Society)
- An empirical study of the naive Bayes classifier
- What the Numbers Say: A Digit-Based Test for Election Fraud (Political Analysis)
- Generating Synthetic Data to Match Data Mining Patterns
- Survival Distributions Satisfying Benford's Law
- The Elements of Statistical Learning
- Regression Shrinkage and Selection via the Lasso