Jaehoon Amir Safavi

Safety, Robustness & Interpretability · 2017

A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Safety, Robustness & Interpretability — 7 citations into it; #1,724 of 2,251 by trust here, #1,907 by citations
• Artificial Intelligence — 6 citations into it
• Computer Networks and Communications — 5 citations into it
• Information Systems — 5 citations into it

Whom Jaehoon Amir Safavi trusts overall

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

1. Blaine Nelson

Who trusts Jaehoon Amir Safavi overall

1. Chris J. M. Yoon
2. Clement Fung
3. Ivan Beschastnikh

Papers from Jaehoon Amir Safavi's perspective

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

1. The security of machine learning
2. Misleading Learners: Co-opting Your Spam Filter
3. Support Vector Machines Under Adversarial Label Noise
4. Poisoning Attacks against Support Vector Machines
5. Systematic Poisoning Attacks on and Defenses for Machine Learning in Healthcare
6. Debugging Machine Learning Tasks
7. Can machine learning be secure?
8. Exploiting Machine Learning to Subvert Your Spam Filter
9. Adversarial learning
10. Paragraph: Thwarting Signature Learning by Training Maliciously

Their papers

• Mitigating Poisoning Attacks on Machine Learning Models: A Data Provenance Based Approach (2017) — 125 citations