Opeyemi Ajibuwa

Artificial Intelligence · 2019

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 — 20 citations into it
• Information Systems — 15 citations into it

Whom Opeyemi Ajibuwa trusts

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

1. Vladimir Naumovich Vapni (in Artificial Intelligence)
2. Jerome H. Friedman (in Artificial Intelligence)
3. Xin-She Yang (in Artificial Intelligence)
4. Gordon V. Cormack (in Information Systems)

Papers from Opeyemi Ajibuwa's perspective

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

1. The Nature of Statistical Learning Theory
2. Random Forests
3. Bagging Predictors
4. Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond
5. Special Invited Paper-Additive logistic regression: A statistical view of boosting
6. An evaluation of Naive Bayesian anti-spam filtering
7. An experimental comparison of naive Bayesian and keyword-based anti-spam filtering with personal e-mail messages (Annual International ACM SIGIR Conference on Research and Development in Information Retrieval)
8. An introduction to ROC analysis
9. Learning to detect phishing emails
10. Improved Boosting Algorithms Using Confidence-rated Predictions

Their papers

• Machine learning for email spam filtering: review, approaches and open research problems (2019) — 475 citations