J. Zurada

Artificial Intelligence · 1992–2009

A researcher in the Science corpus: 10 papers; trusts 21 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 27 citations into it; #24,392 of 35,345 by trust here, #10,667 by citations
• Computer Vision and Pattern Recognition — 12 citations into it; #15,076 of 21,575 by trust here, #10,154 by citations
• Statistical Learning Theory — 10 citations into it
• Reinforcement Learning — 8 citations into it
• Model Architectures — 7 citations into it
• Statistics and Probability — 7 citations into it
• Evaluation & Benchmarks — 6 citations into it
• Algorithms & Complexity — 5 citations into it

Whom J. Zurada trusts overall

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

1. Geoffrey G. Towell
2. Jude W. Shavlik
3. Rudy Setiono
4. David John Cameron MacKay
5. Charles M. Bishop
6. Robert Craig Holte
7. Robert Andrews
8. Andrew P. Bradley
9. Nancy A. Obuchowski
10. Mark W. Craven

Who trusts J. Zurada overall

1. K. Smith‐Miles
2. Pavan Kumar Kankar
3. Shuhui Li
4. Johan A. K. Suykens
5. Lili Zhu
6. Farnaz Fotovatikhah
7. Jatinder N. D. Gupta
8. Young‐Seuk Park
9. Octavio Loyola-González
10. M. Gevrey

Papers from J. Zurada's perspective

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

1. UCI Repository of machine learning databases
2. Fast Effective Rule Induction
3. A Practical Bayesian Framework for Backpropagation Networks
4. Learning from delayed rewards
5. Neural networks for pattern recognition
6. On the Quasi-Minimal Solution of the General Covering Problem
7. Using Sampling and Queries to Extract Rules from Trained Neural Networks
8. Survey and critique of techniques for extracting rules from trained artificial neural networks
9. Infinite Mixtures of Gaussian Process Experts
10. Very Simple Classification Rules Perform Well on Most Commonly Used Datasets

Their papers

• Computational intelligence methods for rule-based data understanding (2004) — 231 citations
• Individualization of pharmacological anemia management using reinforcement learning (2005) — 70 citations
• Incorporating prior knowledge into Q-learning for drug delivery individualization (2005) — 11 citations
• Normalized Mutual Information Feature Selection (2009) — 1,267 citations
• Training neural network classifiers for medical decision making: The effects of imbalanced datasets on classification performance (2008) — 813 citations
• Using clinical information in goal-oriented learning. (2007) — 9 citations
• Reinforcement learning approach to individualization of chronic pharmacotherapy (2005) — 13 citations
• An approach to multimodal biomedical image registration utilizing particle swarm optimization (2004) — 425 citations
• Sensitivity analysis for minimization of input data dimension for feedforward neural network (1994)
• Introduction to artificial neural systems (1992)