Scott Alfeld
Artificial Intelligence · 2016–2017
A researcher in the Science corpus: 2 papers; trusts 15 researchers and is trusted by 6 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 31 citations into it; #15,884 of 35,345 by trust here, #15,236 by citations
- Safety, Robustness & Interpretability — 21 citations into it; #1,249 of 2,251 by trust here, #1,454 by citations
- Computer Networks and Communications — 14 citations into it
- Signal Processing — 11 citations into it
- Privacy & Security — 10 citations into it
- Information Systems — 9 citations into it
- Game & Decision Theory — 7 citations into it
Whom Scott Alfeld trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Blaine Nelson
- Michael Brückner
- Battista Biggio
- Marco Barreno
- Xiaojin Zhu
- Pavel Laskov
- Kymie M. C. Tan
- Nilesh N. Dalvi
- Sanjay Chawla
- Tobias Scheffer
Who trusts Scott Alfeld overall
- Xiaojin Zhu
- Bo Li
- Chang Liu
- Andrea Paudice
- Xinyun Chen
- Gan Sun
- Justin Hsu
- Xuezhou Zhang
- Nicolas Papernot
- Robert D. Nowak
Papers from Scott Alfeld's perspective
Ordered by how strongly the researchers Scott Alfeld trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Nightmare at test time: robust learning by feature deletion
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Adversarial classification
- The security of machine learning
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
Their papers
- Data Poisoning Attacks against Autoregressive Models (2016) — 265 citations
- Explicit Defense Actions Against Test-Set Attacks (2017) — 52 citations