Daniel E. Escudero

Artificial Intelligence · 2018–2019

A researcher in the Science corpus: 4 papers; trusts 55 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 91 citations into it; #25,848 of 35,345 by trust here, #19,873 by citations
• Computational Theory and Mathematics — 36 citations into it; #10,502 of 12,182 by trust here, #6,165 by citations
• Computer Vision and Pattern Recognition — 29 citations into it; #19,469 of 21,575 by trust here, #18,782 by citations
• Information Systems — 25 citations into it; #7,777 of 8,771 by trust here, #7,386 by citations
• Privacy & Security — 21 citations into it; #609 of 709 by trust here, #662 by citations
• Efficiency & Compression — 15 citations into it; #1,118 of 1,264 by trust here, #1,201 by citations
• Computer Networks and Communications — 11 citations into it
• Model Architectures — 6 citations into it

Whom Daniel E. Escudero trusts overall

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

1. Marcel Keller
2. Ivan Bjerre Damgård
3. Alex Krizhevsky
4. Payman Mohassel
5. Ronald Cramer
6. Octavian Catrina
7. Matthieu Courbariaux
8. Ran Canetti
9. Christian Szegedy
10. Sergey Ioffe

Who trusts Daniel E. Escudero overall

1. Marcel Keller
2. Assi Barak
3. Nishant Kumar
4. Ivan Bjerre Damgård
5. Zhicong Huang

Papers from Daniel E. Escudero's perspective

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

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

Their papers

• Secure Evaluation of Quantized Neural Networks (2019) — 159 citations
• SPDℤ2k: Efficient MPC mod 2k for Dishonest Majority (2018) — 192 citations
• New Primitives for Actively-Secure MPC over Rings with Applications to Private Machine Learning (2019) — 182 citations
• SPD Z 2 k : Efficient MPC mod 2 k for Dishonest Majority (2018)