John James Doherty

Artificial Intelligence · 2017–2019

A researcher in the Science corpus: 2 papers; trusts 37 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 35 citations into it; #16,461 of 35,345 by trust here, #26,682 by citations
• Computational Theory and Mathematics — 24 citations into it; #5,276 of 12,182 by trust here, #7,501 by citations
• Control and Systems Engineering — 5 citations into it
• Management Science and Operations Research — 5 citations into it
• Mechanical Engineering — 5 citations into it

Whom John James Doherty trusts overall

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

1. Yaochu Jin
2. Michael L. Stein
3. Tinkle Chugh
4. Handing Wang
5. Bo Liu
6. Leo Breiman
7. Peter John Fleming
8. Joaquín Derrac
9. Sugato Basu
10. Joshua D. Knowles

Who trusts John James Doherty overall

1. Handing Wang
2. Yaochu Jin
3. Yanan Sun

Papers from John James Doherty's perspective

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

1. Bagging Predictors
2. A framework for evolutionary optimization with approximate fitness functions (IEEE Transactions on Evolutionary Computation)
3. ParEGO: a hybrid algorithm with on-line landscape approximation for expensive multiobjective optimization problems (IEEE Transactions on Evolutionary Computation)
4. Single- and multiobjective evolutionary optimization assisted by Gaussian random field metamodels (IEEE Transactions on Evolutionary Computation)
5. A Survey on Transfer Learning
6. Efficient Global Optimization of Expensive Black-Box Functions
7. Query by committee
8. Large sample properties of simulations using latin hypercube sampling
9. Surrogate-assisted evolutionary computation: Recent advances and future challenges
10. Ensemble of surrogates

Their papers

• Committee-Based Active Learning for Surrogate-Assisted Particle Swarm Optimization of Expensive Problems (2017) — 356 citations
• Offline Data-Driven Evolutionary Optimization Using Selective Surrogate Ensembles (2019) — 213 citations