Albert Cheu
Artificial Intelligence · 2018–2021
A researcher in the Science corpus: 8 papers; trusts 67 researchers and is trusted by 28 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 154 citations into it; #8,461 of 35,345 by trust here, #15,866 by citations
- Privacy & Security — 125 citations into it; #118 of 709 by trust here, #175 by citations
- Computational Theory and Mathematics — 24 citations into it
- Statistics and Probability — 22 citations into it
- Safety, Robustness & Interpretability — 16 citations into it
- Sociology and Political Science — 15 citations into it
- Algorithms & Complexity — 12 citations into it
- Electrical and Electronic Engineering — 12 citations into it; #2,900 of 16,539 by trust here, #10,714 by citations
Whom Albert Cheu trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Cynthia Dwork
- Kobbi Nissim
- Adam D. Smith
- Badih Ghazi
- Mark Bun
- John C. Duchi
- Ú. Erlingsson
- Raef Bassily
- Shiva Prasad Kasiviswanathan
- Victor Balcer
Who trusts Albert Cheu overall
- Badih Ghazi
- Borja Balle
- James Bell
- Ravi Kumar
- Amos Beimel
- Peter Kairouz
- Vitaly Feldman
- Victor Balcer
- Kobbi Nissim
- Pasin Manurangsi
Papers from Albert Cheu's perspective
Ordered by how strongly the researchers Albert Cheu trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Calibrating Noise to Sensitivity in Private Data Analysis
- ImageNet classification with deep convolutional neural networks
- Gradient-based learning applied to document recognition
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Learning Multiple Layers of Features from Tiny Images
- Revealing information while preserving privacy
- Attention is All you Need (Neural Information Processing Systems)
- RAPPOR: Randomized Aggregatable Privacy-Preserving Ordinal Response
- Long Short-Term Memory
Their papers
- Separating Local & Shuffled Differential Privacy via Histograms (2019) — 78 citations
- Differentially Private Histograms in the Shuffle Model from Fake Users (2021) — 42 citations
- The limits of pan privacy and shuffle privacy for learning and estimation (2020) — 26 citations
- Connecting Robust Shuffle Privacy and Pan-Privacy (2020) — 47 citations
- Private Query Release Assisted by Public Data (2020) — 53 citations
- Manipulation Attacks in Local Differential Privacy (2019) — 124 citations
- Distributed Differential Privacy via Shuffling (2018) — 433 citations
- Distributed Differential Privacy via Mixnets (2018) — 21 citations