Tudor Dumitras
Artificial Intelligence · 2012–2020
A researcher in the Science corpus: 9 papers; trusts 253 researchers and is trusted by 7 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 157 citations into it
- Safety, Robustness & Interpretability — 103 citations into it; #2,151 of 2,251 by trust here, #737 by citations
- Computer Vision and Pattern Recognition — 58 citations into it
- Signal Processing — 47 citations into it; #4,774 of 7,572 by trust here, #1,904 by citations
- Computer Networks and Communications — 46 citations into it; #7,395 of 9,886 by trust here, #4,950 by citations
- Information Systems — 26 citations into it; #6,393 of 8,771 by trust here, #4,518 by citations
- Privacy & Security — 19 citations into it
- Efficiency & Compression — 16 citations into it
Whom Tudor Dumitras trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Krizhevsky
- Geoffrey E. Hinton
- Diederik P. Kingma
- Kaiming He
- Christian Szegedy
- Yoshua Bengio
- Yann LeCun
- Karen Simonyan
- Ilya Sutskever
- Ian J. Goodfellow
Who trusts Tudor Dumitras overall
Papers from Tudor Dumitras's perspective
Ordered by how strongly the researchers Tudor Dumitras trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Learning Multiple Layers of Features from Tiny Images
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- When Does Machine Learning FAIL? Generalized Transferability for Evasion and Poisoning Attacks (2018) — 323 citations
- On the Effectiveness of Mitigating Data Poisoning Attacks with Gradient Shaping (2020) — 157 citations
- A Panda? No, It's a Sloth: Slowdown Attacks on Adaptive Multi-Exit Neural Network Inference (2020) — 88 citations
- Shallow-Deep Networks: Understanding and Mitigating Network Overthinking (2018) — 395 citations
- Poison Frogs! Targeted Clean-Label Poisoning Attacks on Neural Networks (2018) — 1,286 citations
- Summoning Demons: The Pursuit of Exploitable Bugs in Machine Learning (2017) — 20 citations
- FeatureSmith: Automatically Engineering Features for Malware Detection by Mining the Security Literature (2016) — 114 citations
- Vulnerability Disclosure in the Age of Social Media: Exploiting Twitter for Predicting Real-World Exploits (2015) — 331 citations
- Before we knew it: an empirical study of zero-day attacks in the real world (2012) — 727 citations