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researcher

Ross Anderson

22 papers hereh-index 152.1k citations27 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author7
  • last author15

Across the 22 of 22 papers where every author was matched, so the position is known.

fields
  • cs.LG10
  • cs.CR7
  • cs.CY2
  • cs.CL1
  • cs.CV1
  • cs.SI1
same name
  • Ross Anderson — 7 papers, h 6
  • Ross Anderson — 4 papers, h 4
  • Ross Anderson — 1 paper, h 3
  • Ross Anderson — 1 paper, h 2

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20182023
most citedThe Curse of Recursion: Training on Generated Data Makes Models Forget

158 citations · 271 across the 18 of their papers we have counts for

collaborators
Showing 2021Show all

4 papers · 1 filter

cs.SI2021★ 2 cited

ExtremeBB: A Database for Large-Scale Research into Online Hate, Harassment, the Manosphere and Extremism

Anh V. Vu, Lydia Wilson, Yi Ting Chua +2

We introduce ExtremeBB, a textual database of over 53.5M posts made by 38.5k users on 12 extremist bulletin board forums promoting online hate, harassment, the manosphere and other…

cs.CL2021★ 4 cited

Bad Characters: Imperceptible NLP Attacks

Nicholas Boucher, Ilia Shumailov, Ross Anderson +1

Several years of research have shown that machine-learning systems are vulnerable to adversarial examples, both in theory and in practice. Until now, such attacks have primarily ta…

cs.LG2021★ 3 cited

Markpainting: Adversarial Machine Learning meets Inpainting

David Khachaturov, Ilia Shumailov, Yiren Zhao +2

Inpainting is a learned interpolation technique that is based on generative modeling and used to populate masked or missing pieces in an image; it has wide applications in picture…

cs.LG2021★ 7 cited

Manipulating SGD with Data Ordering Attacks

Ilia Shumailov, Zakhar Shumaylov, Dmitry Kazhdan +4

Machine learning is vulnerable to a wide variety of attacks. It is now well understood that by changing the underlying data distribution, an adversary can poison the model trained…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.