Rachel Cummings

Artificial Intelligence · 2011–2019

A researcher in the Science corpus: 9 papers; trusts 32 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 428 citations into it
• Privacy & Security — 234 citations into it
• Optimization & Training — 92 citations into it
• Computer Networks and Communications — 55 citations into it
• Computational Theory and Mathematics — 54 citations into it
• Statistics and Probability — 41 citations into it
• Sociology and Political Science — 36 citations into it
• Management Science and Operations Research — 32 citations into it

Whom Rachel Cummings trusts overall

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

1. Cynthia Dwork
2. Frank McSherry
3. Avrim Blum
4. Moritz Hardt
5. Kobbi Nissim
6. Aaron Roth
7. Adam D. Smith
8. Raef Bassily
9. Yajun Mei
10. Shai Shalev-Shwartz

Who trusts Rachel Cummings overall

1. Ryan M. Rogers
2. Aaron Roth
3. Kyomin Jung

Papers from Rachel Cummings's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Gradient-based learning applied to document recognition
4. Learning Multiple Layers of Features from Tiny Images
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Long Short-Term Memory
7. ImageNet: A large-scale hierarchical image database
8. Attention is All you Need (Neural Information Processing Systems)
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Going deeper with convolutions

Their papers

• Advances and Open Problems in Federated Learning (2019) — 9,019 citations
• On the Compatibility of Privacy and Fairness (2019) — 181 citations
• Differential Privacy for Growing Databases (2018) — 46 citations
• Defining and Designing Fair Algorithms (2018) — 8 citations
• Differentially Private Change-Point Detection (2018) — 35 citations
• The Role of Differential Privacy in GDPR Compliance (2018)
• Adaptive Learning with Robust Generalization Guarantees (2016) — 63 citations
• The Possibilities and Limitations of Private Prediction Markets (2016) — 20 citations
• Influence Maximization in Social Networks When Negative Opinions May Emerge and Propagate (2011) — 417 citations