Jeff Huang
Information Systems · ACM Conference on Hypertext & Social Media · 2009–2018
A researcher in the Science corpus: 4 papers; trusts 37 researchers and is trusted by 12 researchers here, as inferred from the citation graph.
Subfields
- Information Systems — 34 citations into it; #2,188 of 8,771 by trust here, #4,341 by citations
- Signal Processing — 16 citations into it; #2,696 of 7,572 by trust here, #6,083 by citations
- Artificial Intelligence — 15 citations into it
- Software — 14 citations into it; #359 of 1,227 by trust here, #965 by citations
- Computer Vision and Pattern Recognition — 11 citations into it
- Natural Language Processing — 10 citations into it
- Information Retrieval & Search — 6 citations into it
- Model Architectures — 5 citations into it
Whom Jeff Huang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Thorsten Joachims
- Rosie Jones
- Greg Pass
- Yoshua Bengio
- Ricardo A. Baeza-Yates
- Jaime Teevan
- Filip Radlinski
- Michail Vlachos
- Eytan Adar
- Chanchal Kumar Roy
Who trusts Jeff Huang overall
- Ruhi Sarikaya
- Yiqun Liu
- Lutz Büch
- Jian Zhang
- Mohamed M. Mostafa
- Yi Li
- Wenhan Wang
- Rodrigo Nogueira
- Jacob Ratkiewicz
- Fabian Abel
Papers from Jeff Huang's perspective
Ordered by how strongly the researchers Jeff Huang trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
Their papers
- Conversational tagging in twitter (2010) — 312 citations
- Analyzing and evaluating query reformulation strategies in web search logs (2009) — 328 citations
- DeepSim: deep learning code functional similarity (2018) — 288 citations
- No clicks, no problem: using cursor movements to understand and improve search (2011) — 327 citations