Alisa Chang

Artificial Intelligence · 2021

A researcher in the Science corpus: 1 paper; trusts 18 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 33 citations into it
• Privacy & Security — 23 citations into it
• Computational Theory and Mathematics — 6 citations into it

Whom Alisa Chang trusts overall

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

1. Badih Ghazi
2. Sariel Har-Peled
3. Uri Stemmer
4. Kobbi Nissim
5. Ú. Erlingsson
6. Cynthia Dwork
7. Moses Charikar
8. Borja Balle
9. Ravi Kumar
10. David Arthur

Papers from Alisa Chang's perspective

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

1. Calibrating Noise to Sensitivity in Private Data Analysis
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Our Data, Ourselves: Privacy Via Distributed Noise Generation
5. Gradient-based learning applied to document recognition
6. RAPPOR: Randomized Aggregatable Privacy-Preserving Ordinal Response
7. ImageNet classification with deep convolutional neural networks
8. Amplification by Shuffling: From Local to Central Differential Privacy via Anonymity
9. Attention is All you Need (Neural Information Processing Systems)
10. The Privacy Blanket of the Shuffle Model

Their papers

• Locally Private k-Means in One Round (2021) — 42 citations