Hamish Ivey-Law

Artificial Intelligence · 2017–2018

A researcher in the Science corpus: 2 papers; trusts 6 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 31 citations into it; #24,964 of 35,345 by trust here, #10,798 by citations
• Management Science and Operations Research — 11 citations into it
• Privacy & Security — 11 citations into it; #600 of 709 by trust here, #342 by citations
• Algorithms & Complexity — 5 citations into it

Whom Hamish Ivey-Law trusts overall

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

1. Peter Christen
2. Richard Nock
3. Giorgio Patrini
4. R. Schnell
5. Pascal Paillier
6. Yoshinori Aono

Who trusts Hamish Ivey-Law overall

1. Yang Liu
2. Qiang Yang
3. Qinbin Li

Papers from Hamish Ivey-Law's perspective

Ordered by how strongly the researchers Hamish Ivey-Law trusts endorse each paper. Same corpus, a different order for every researcher.

1. Gradient-based learning applied to document recognition
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Differential Privacy: A Survey of Results
4. ImageNet classification with deep convolutional neural networks
5. Convexity, Classification, and Risk Bounds
6. Rademacher and Gaussian Complexities: Risk Bounds and Structural Results
7. Learning Multiple Layers of Features from Tiny Images
8. Minimizing finite sums with the stochastic average gradient
9. Fair exchange with a semi-trusted third party (extended abstract)
10. Matrix analysis

Their papers

• Private federated learning on vertically partitioned data via entity resolution and additively homomorphic encryption (2017) — 622 citations
• Entity Resolution and Federated Learning get a Federated Resolution (2018) — 95 citations