Ignazio Pillai

Artificial Intelligence · 2006–2016

A researcher in the Science corpus: 6 papers; trusts 36 researchers and is trusted by 8 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 53 citations into it; #16,676 of 35,345 by trust here, #13,962 by citations
• Safety, Robustness & Interpretability — 32 citations into it; #1,774 of 2,251 by trust here, #1,819 by citations
• Computer Networks and Communications — 30 citations into it; #4,245 of 9,886 by trust here, #2,613 by citations
• Signal Processing — 27 citations into it; #3,381 of 7,572 by trust here, #1,904 by citations
• Information Systems — 25 citations into it; #4,143 of 8,771 by trust here, #3,402 by citations
• Computer Vision and Pattern Recognition — 10 citations into it; #18,834 of 21,575 by trust here, #18,266 by citations
• Game & Decision Theory — 8 citations into it
• Natural Language Processing — 8 citations into it

Whom Ignazio Pillai trusts overall

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

1. Fabrizio Sebastiani
2. Yiming Yang
3. Chih-Jen Lin
4. Battista Biggio
5. Grigorios Tsoumakas
6. David D. Lewis
7. Michael Brückner
8. Jason D. M. Rennie
9. Roberto Perdisci
10. Yann LeCun

Who trusts Ignazio Pillai overall

1. Battista Biggio
2. Fabio Roli
3. Nicholas Carlini
4. Joseph Gardiner
5. Thiago S. Guzella
6. Giorgio Fumera
7. Mark Dredze
8. Shishir Nagaraja
9. Shaik Mustafa
10. Qiang Liu

Papers from Ignazio Pillai's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Gradient-based learning applied to document recognition
4. Attention is All you Need (Neural Information Processing Systems)
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Long Short-Term Memory
7. Learning Multiple Layers of Features from Tiny Images
8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
9. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
10. ImageNet: A large-scale hierarchical image database

Their papers

• Is data clustering in adversarial settings secure? (2013) — 135 citations
• Randomized Prediction Games for Adversarial Machine Learning (2016) — 64 citations
• Poisoning Complete-Linkage Hierarchical Clustering (2014) — 62 citations
• Multi-label classification with a reject option (2013) — 60 citations
• A survey and experimental evaluation of image spam filtering techniques (2011) — 94 citations
• Spam Filtering Based On The Analysis Of Text Information Embedded Into Images (2006) — 165 citations