Luca Oneto

Artificial Intelligence · 2012–2020

A researcher in the Science corpus: 9 papers; trusts 227 researchers and is trusted by 7 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 167 citations into it; #23,944 of 35,345 by trust here, #11,192 by citations
• AI Ethics, Fairness & Society — 83 citations into it; #334 of 494 by trust here, #196 by citations
• Safety Research — 79 citations into it; #3,442 of 5,829 by trust here, #1,224 by citations
• Safety, Robustness & Interpretability — 77 citations into it
• Computer Vision and Pattern Recognition — 63 citations into it; #20,875 of 21,575 by trust here, #10,677 by citations
• Sociology and Political Science — 55 citations into it
• Statistical Learning Theory — 39 citations into it
• Statistics and Probability — 38 citations into it

Whom Luca Oneto trusts overall

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

1. Faisal Kamiran
2. Peter L. Bartlett
3. Toon Calders
4. Michael P. Kim
5. Shahar Mendelson
6. Muhammad Bilal Zafar
7. Yuhai Wu
8. John Shawe-Taylor
9. Sara Hajian
10. Olivier Bousquet

Who trusts Luca Oneto overall

1. Silvia Chiappa
2. Michele Donini
3. Karthik S. Gurumoorthy
4. Wenchao Jiang
5. Ben Hutchinson
6. Chenyue Wu
7. Arjun Nitin Bhagoji
8. Andrew Cotter
9. Robert C. Williamson
10. Jihun Hamm

Papers from Luca Oneto's perspective

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

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

Their papers

• Empirical Risk Minimization under Fairness Constraints (2018) — 500 citations
• Human Activity Recognition on Smartphones Using a Multiclass Hardware-Friendly Support Vector Machine (2012) — 982 citations
• Transition-Aware Human Activity Recognition Using Smartphones (2016) — 734 citations
• Fairness in Machine Learning (2020) — 557 citations
• Taking Advantage of Multitask Learning for Fair Classification (2018) — 70 citations
• Machine learning approaches for improving condition-based maintenance of naval propulsion plants (2016) — 198 citations
• Tikhonov, Ivanov and Morozov regularization for support vector machine learning (2016) — 69 citations
• A Public Domain Dataset for Human Activity Recognition using Smartphones (2013) — 2,591 citations
• The 'K' in K-fold Cross Validation (2012) — 367 citations