Hao Chen
Artificial Intelligence · with Laine · 2016–2019
A researcher in the Science corpus: 11 papers; trusts 92 researchers and is trusted by 18 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 235 citations into it; #9,193 of 35,345 by trust here, #11,072 by citations
- Computational Theory and Mathematics — 135 citations into it; #5,546 of 12,182 by trust here, #5,046 by citations
- Privacy & Security — 76 citations into it; #508 of 709 by trust here, #642 by citations
- Information Systems — 39 citations into it
- Computer Vision and Pattern Recognition — 27 citations into it
- Computer Networks and Communications — 19 citations into it
- Algorithms & Complexity — 10 citations into it
- Mathematical Optimization — 6 citations into it
Whom Hao Chen trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Craig Gentry
- Zvika Brakerski
- Oded Regev
- Junfeng Fan
- Shai Halevi
- Vinod Vaikuntanathan
- David Harvey
- Vadim Lyubashevsky
- Benny Pinkas
- Frederik Vercauteren
Who trusts Hao Chen overall
- Sebastian Angel
- Kim Laine
- Zhicong Huang
- Tancrède Lepoint
- Asra Ali
- Sarvar Patel
- Chaoyue Niu
- A. Al Badawi
- Vladimir Kolesnikov
- Sujoy Sinha Roy
Papers from Hao Chen's perspective
Ordered by how strongly the researchers Hao Chen trusts endorse each paper. Same corpus, a different order for every researcher.
- Fully homomorphic encryption using ideal lattices
- On Ideal Lattices and Learning with Errors over Rings
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Public-Key Cryptosystems Based on Composite Degree Residuosity Classes
- Gradient-based learning applied to document recognition
- Learning Multiple Layers of Features from Tiny Images
- ImageNet classification with deep convolutional neural networks
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Fully Homomorphic Encryption from Ring-LWE and Security for Key Dependent Messages
Their papers
- Homomorphic Encryption Standard (2019) — 295 citations
- PIR with Compressed Queries and Amortized Query Processing (2018) — 364 citations
- Fast Private Set Intersection from Homomorphic Encryption (2017) — 461 citations
- Efficient Multi-Key Homomorphic Encryption with Packed Ciphertexts with Application to Oblivious Neural Network Inference (2019) — 240 citations
- Labeled PSI from Fully Homomorphic Encryption with Malicious Security (2018) — 250 citations
- XONN: XNOR-based Oblivious Deep Neural Network Inference (2019) — 317 citations
- CHET: Compiler and Runtime for Homomorphic Evaluation of Tensor Programs (2018) — 14 citations
- SECURITY OF HOMOMORPHIC ENCRYPTION (2017)
- Simple Encrypted Arithmetic Library-SEAL (2017)
- Simple Encrypted Arithmetic Library v2.3.0 (2017) — 88 citations
- Simple Encrypted Arithmetic Library - SEAL v2.1 (2016) — 307 citations