Rudy Setiono

Artificial Intelligence · 1995–2008

A researcher in the Science corpus: 8 papers; trusts 22 researchers and is trusted by 25 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 21 citations into it; #6,960 of 35,345 by trust here, #9,760 by citations
• Statistical Learning Theory — 15 citations into it
• Algorithms & Complexity — 10 citations into it
• Safety, Robustness & Interpretability — 9 citations into it
• Information Systems — 6 citations into it
• Optimization & Training — 5 citations into it

Whom Rudy Setiono trusts overall

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

1. Geoffrey G. Towell
2. Roberto Battiti
3. J. Ross Quinlan
4. Jude W. Shavlik
5. John E. Dennis Jr.
6. Robert Andrews
7. Joachim Diederich
8. Mark W. Craven
9. Usama M. Fayyad
10. David John Cameron MacKay

Who trusts Rudy Setiono overall

1. Tameru Hailesilassie
2. Gethsiyal Augasta M
3. Thangairulappan Kathirvalavakumar
4. Marko Robnik-Sikonja
5. Wlodzislaw Duch
6. Hussein A. Abbass
7. Leilani H. Gilpin
8. Mariusz Bojarski
9. Emilio Carrizosa
10. Humar Kahramanli

Papers from Rudy Setiono's perspective

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

1. The Nature of Statistical Learning Theory
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Attention is All you Need (Neural Information Processing Systems)
5. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
6. Density Estimation for Statistics and Data Analysis
7. Using Sampling and Queries to Extract Rules from Trained Neural Networks
8. Gradient-based learning applied to document recognition
9. Long Short-Term Memory
10. Survey and critique of techniques for extracting rules from trained artificial neural networks

Their papers

• Rule Extraction from Support Vector Machines: An Overview of Issues and Application in Credit Scoring (2008) — 99 citations
• Product-, corporate-, and country-image dimensions and purchase behavior: A multicountry analysis (2004) — 532 citations
• Computational intelligence methods for rule-based data understanding (2004) — 231 citations
• FERNN: An Algorithm for Fast Extraction of Rules from Neural Networks (2004) — 155 citations
• Using Neural Network Rule Extraction and Decision Tables for Credit - Risk Evaluation (2003) — 556 citations
• Extracting -of- Rules from Trained Neural Networks (2000) — 94 citations
• Effective Data Mining Using Neural Networks (1996)
• Understanding Neural Networks via Rule Extraction (1995)