P. Pintelas

Artificial Intelligence · 2004–2020

A researcher in the Science corpus: 5 papers; trusts 29 researchers and is trusted by 8 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 52 citations into it; #18,106 of 35,345 by trust here, #16,166 by citations
• Information Systems — 17 citations into it
• Evaluation & Benchmarks — 14 citations into it
• Statistical Learning Theory — 13 citations into it
• Computational Theory and Mathematics — 10 citations into it
• Optimization & Training — 7 citations into it
• Algorithms & Complexity — 6 citations into it

Whom P. Pintelas trusts overall

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

1. Thomas G. Dietterich
2. William W. Cohen
3. J. Ross Quinlan
4. Leo Breiman
5. C. Burges
6. Yoav Freund
7. Sreerama K. Murthy
8. Pedro M. Domingos
9. Dietrich Wettschereck
10. Foster J. Provost

Who trusts P. Pintelas overall

1. Kwetishe Joro Danjuma
2. Ayanna M. Howard
3. Eduardo Almeida Soares
4. Paulo Cortez
5. Swasti Singhal
6. Jonathan J. Davis

Papers from P. Pintelas's perspective

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

1. Long Short-Term Memory
2. ImageNet classification with deep convolutional neural networks
3. Gradient-based learning applied to document recognition
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. UCI Repository of machine learning databases
6. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
7. Bagging Predictors
8. A decision-theoretic generalization of on-line learning and an application to boosting
9. ImageNet: A large-scale hierarchical image database
10. Attention is All you Need (Neural Information Processing Systems)

Their papers

• A CNN–LSTM model for gold price time-series forecasting (2020) — 766 citations
• Data Preprocessing for Supervised Leaning (2007) — 1,041 citations
• Machine learning: a review of classification and combining techniques (2006) — 1,442 citations
• Handling imbalanced datasets: A review (2006) — 1,061 citations
• PREDICTING STUDENTS' PERFORMANCE IN DISTANCE LEARNING USING MACHINE LEARNING TECHNIQUES (2004) — 333 citations