Haitao Zheng
Artificial Intelligence · Mob. Networks Appl. · 2005–2023
A researcher in the Science corpus: 21 papers; trusts 288 researchers and is trusted by 16 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 228 citations into it; #22,893 of 35,345 by trust here, #7,728 by citations
- Safety, Robustness & Interpretability — 125 citations into it
- Computer Vision and Pattern Recognition — 112 citations into it
- Computer Networks and Communications — 101 citations into it; #3,087 of 9,886 by trust here, #2,478 by citations
- Signal Processing — 83 citations into it; #5,238 of 7,572 by trust here, #805 by citations
- Information Systems — 68 citations into it
- Electrical and Electronic Engineering — 26 citations into it; #3,716 of 16,539 by trust here, #7,520 by citations
- Hardware and Architecture — 25 citations into it
Whom Haitao Zheng trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Diederik P. Kingma
- Alex Krizhevsky
- Yoshua Bengio
- Yann LeCun
- Ian J. Goodfellow
- Kaiming He
- Ilya Sutskever
- Christian Szegedy
- Nicholas Carlini
Who trusts Haitao Zheng overall
- Ian F. Akyildiz
- Jean-Pierre Hubaux
- Won-Yeol Lee
- Beibei Wang
- Yige Li
- Yinzhi Cao
- Shawn Shan
- Rahul Urgaonkar
- David Marco Sommer
- Ying-Chang Liang
Papers from Haitao Zheng's perspective
Ordered by how strongly the researchers Haitao Zheng trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Learning Multiple Layers of Features from Tiny Images
- Going deeper with convolutions
Their papers
- GLAZE: Protecting Artists from Style Mimicry by Text-to-Image Models (2023) — 295 citations
- Neural Cleanse: Identifying and Mitigating Backdoor Attacks in Neural Networks (2019) — 1,894 citations
- Distributed spectrum allocation via local bargaining (2005) — 425 citations
- Utilization and fairness in spectrum assignment for opportunistic spectrum access (2006) — 573 citations
- Mirror mirror on the ceiling: flexible wireless links for data centers (2012) — 340 citations
- "Will Check-in for Badges": Understanding Bias and Misbehavior on Location-Based Social Networks (2021) — 39 citations
- On the validity of geosocial mobility traces (2013) — 59 citations
- Automated Crowdturfing Attacks and Defenses in Online Review Systems (2017) — 169 citations
- A General Framework for Wireless Spectrum Auctions (2007) — 335 citations
- eBay in the Sky: strategy-proof wireless spectrum auctions (2008) — 486 citations
- TRUST: A General Framework for Truthful Double Spectrum Auctions (2009) — 513 citations
- Defending against Sybil Devices in Crowdsourced Mapping Services (2015) — 98 citations
- Northeastern University (2021) — 302 citations
- Fawkes: Protecting Privacy against Unauthorized Deep Learning Models (2020) — 307 citations
- Latent Backdoor Attacks on Deep Neural Networks (2019) — 478 citations
- With Great Training Comes Great Vulnerability: Practical Attacks against Transfer Learning (2018) — 126 citations
- Poster: Defending against Sybil Devices in Crowdsourced Mapping Services (2016) — 25 citations
- Packet-Level Telemetry in Large Datacenter Networks (2015) — 397 citations
- Man vs. Machine: Practical Adversarial Detection of Malicious Crowdsourcing Workers (2014) — 187 citations
- On the Embeddability of Random Walk Distances (2013) — 36 citations