Kevin Chen-Chuan Chang
Artificial Intelligence · 2002–2022
A researcher in the Science corpus: 20 papers; trusts 531 researchers and is trusted by 46 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 319 citations into it; #6,263 of 35,345 by trust here, #5,120 by citations
- Graph Learning — 123 citations into it; #427 of 693 by trust here, #330 by citations
- Computer Vision and Pattern Recognition — 113 citations into it; #8,771 of 21,575 by trust here, #12,992 by citations
- Statistical and Nonlinear Physics — 100 citations into it; #3,910 of 10,127 by trust here, #1,166 by citations
- Representation & Self-Supervised Learning — 89 citations into it
- Natural Language Processing — 74 citations into it
- Large Language Models — 54 citations into it
- Information Systems — 46 citations into it; #914 of 8,771 by trust here, #2,203 by citations
Whom Kevin Chen-Chuan Chang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Yoshua Bengio
- Diederik P. Kingma
- Ilya Sutskever
- Alex Krizhevsky
- Yann LeCun
- Kaiming He
- Jimmy Ba
- Alex Graves
- Sepp Hochreiter
Who trusts Kevin Chen-Chuan Chang overall
- Ihab F. Ilyas
- Yi Luo
- Nicolas Bruno
- Chengkai Li
- Mohamed A. Soliman
- George Beskales
- Shehroz S. Khan
- Jessa Bekker
- Xuemin Lin
- Hwanjo Yu
Papers from Kevin Chen-Chuan Chang's perspective
Ordered by how strongly the researchers Kevin Chen-Chuan Chang 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)
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- 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)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- Towards Reasoning in Large Language Models: A Survey (2022) — 934 citations
- Are Large Pre-Trained Language Models Leaking Your Personal Information? (2022) — 297 citations
- Statistical schema matching across web query interfaces (2003) — 380 citations
- PEBL: Web page classification without negative examples (2004) — 301 citations
- Top-k Query Processing in Uncertain Databases (2007) — 479 citations
- PEBL: positive example based learning for Web page classification using SVM (2002) — 333 citations
- Geom-GCN: Geometric Graph Convolutional Networks (2020) — 1,493 citations
- Distance-Aware DAG Embedding for Proximity Search on Heterogeneous Graphs (2018) — 35 citations
- Subgraph-augmented Path Embedding for Semantic User Search on Heterogeneous Social Network (2018) — 28 citations
- A Comprehensive Survey of Graph Embedding: Problems, Techniques, and Applications (2017) — 1,965 citations
- Topological Recurrent Neural Network for Diffusion Prediction (2017) — 203 citations
- Learning Community Embedding with Community Detection and Node Embedding on Graphs (2017) — 395 citations
- Semantic Proximity Search on Heterogeneous Graph by Proximity Embedding (2017) — 71 citations
- From Node Embedding To Community Embedding (2016) — 34 citations
- TEDAS: A Twitter-based Event Detection and Analysis System (2012) — 475 citations
- Towards social user profiling: unified and discriminative influence model for inferring home locations (2012) — 354 citations
- Accessing the deep web (2007) — 364 citations
- RankSQL: query algebra and optimization for relational top-k queries (2005) — 331 citations
- Structured databases on the web: observations and implications (2004) — 416 citations
- Minimal probing: supporting expensive predicates for top-k queries (2002) — 328 citations