Pasin Manurangsi
Artificial Intelligence · 2018–2021
A researcher in the Science corpus: 8 papers; trusts 108 researchers and is trusted by 11 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 237 citations into it; #10,207 of 35,345 by trust here, #9,641 by citations
- Privacy & Security — 157 citations into it; #265 of 709 by trust here, #351 by citations
- Computational Theory and Mathematics — 37 citations into it
- Optimization & Training — 30 citations into it
- Computer Science Applications — 29 citations into it
- Statistics and Probability — 28 citations into it
- Sociology and Political Science — 25 citations into it
- Safety, Robustness & Interpretability — 21 citations into it
Whom Pasin Manurangsi trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Badih Ghazi
- Cynthia Dwork
- Ú. Erlingsson
- David Haussler
- Borja Balle
- Kobbi Nissim
- Ilya Mironov
- Alon Brutzkus
- Frank McSherry
- Albert Cheu
Who trusts Pasin Manurangsi overall
Papers from Pasin Manurangsi's perspective
Ordered by how strongly the researchers Pasin Manurangsi trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet classification with deep convolutional neural networks
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- Learning Multiple Layers of Features from Tiny Images
- Long Short-Term Memory
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- ImageNet: A large-scale hierarchical image database
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
Their papers
- Large-Scale Differentially Private BERT (2021) — 162 citations
- The Computational Complexity of Training ReLU(s) (2018) — 47 citations
- Private Aggregation from Fewer Anonymous Messages (2019) — 57 citations
- Locally Private k-Means in One Round (2021) — 42 citations
- Differentially Private Aggregation in the Shuffle Model: Almost Central Accuracy in Almost a Single Message (2021) — 45 citations
- On Distributed Differential Privacy and Counting Distinct Elements (2020) — 35 citations
- Private Counting from Anonymous Messages: Near-Optimal Accuracy with Vanishing Communication Overhead (2020) — 60 citations
- Pure Differentially Private Summation from Anonymous Messages (2020) — 51 citations