Quanyan Zhu

Artificial Intelligence · 2011–2017

A researcher in the Science corpus: 7 papers; trusts 27 researchers and is trusted by 8 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 27 citations into it; #12,808 of 35,345 by trust here, #25,040 by citations
• Computer Networks and Communications — 19 citations into it; #2,642 of 9,886 by trust here, #4,128 by citations
• Privacy & Security — 17 citations into it
• Information Systems — 13 citations into it
• Electrical and Electronic Engineering — 12 citations into it
• Computational Theory and Mathematics — 7 citations into it
• Safety, Robustness & Interpretability — 6 citations into it
• Algorithms & Complexity — 5 citations into it

Whom Quanyan Zhu trusts overall

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

1. Shai Shalev-Shwartz
2. Michael Collins
3. Leslie G. Valiant
4. Muthu Dayalan
5. Pedro A. Forero
6. Kobbi Nissim
7. Cynthia Dwork
8. Frank McSherry
9. Ryan T. McDonald
10. Shiva Prasad Kasiviswanathan

Who trusts Quanyan Zhu overall

1. Xueru Zhang
2. Yaochen Hu
3. Mohammad Mahdi Khalili
4. Peng Liu
5. Zonghao Huang
6. Mengmeng Yu
7. M. Liu
8. Milad Nasr
9. Reza Shokri
10. John S. Vardakas

Papers from Quanyan Zhu's perspective

Ordered by how strongly the researchers Quanyan Zhu 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. Learning Multiple Layers of Features from Tiny Images
7. Attention is All you Need (Neural Information Processing Systems)
8. ImageNet: A large-scale hierarchical image database
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Calibrating Noise to Sensitivity in Private Data Analysis

Their papers

• Dependable Demand Response Management in the Smart Grid: A Stackelberg Game Approach (2013) — 743 citations
• Risk-sensitive mean field stochastic differential games (2011) — 80 citations
• Game theory meets network security and privacy (2013) — 834 citations
• Dynamic Differential Privacy for ADMM-Based Distributed Classification Learning (2017) — 194 citations
• A Dual Perturbation Approach for Differential Private ADMM-Based Distributed Empirical Risk Minimization (2016) — 17 citations
• Secure and resilient distributed machine learning under adversarial environments (2015) — 34 citations
• Game-Theoretic Methods for Robustness, Security, and Resilience of Cyberphysical Control Systems: Games-in-Games Principle for Optimal Cross-Layer Resilient Control Systems (2015) — 405 citations