Allison Chang
Artificial Intelligence · 2012
A researcher in the Science corpus: 4 papers; trusts 66 researchers and is trusted by 2 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 54 citations into it; #26,646 of 35,345 by trust here, #29,412 by citations
- Information Systems — 31 citations into it; #6,149 of 8,771 by trust here, #7,107 by citations
- Statistical Learning Theory — 25 citations into it
- Computational Theory and Mathematics — 22 citations into it; #9,201 of 12,182 by trust here, #8,756 by citations
- Algorithms & Complexity — 18 citations into it
- Statistics and Probability — 11 citations into it
- Information Retrieval & Search — 10 citations into it
- Computer Vision and Pattern Recognition — 9 citations into it
Whom Allison Chang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Cynthia Rudin
- Vladimir Naumovich Vapnik
- Rakesh Agrawal
- Thorsten Joachims
- Yoav Freund
- Niko Speybroeck
- Vladimir Naumovich Vapni
- Jiawei Han
- Andrew P. Bradley
- Dimitris J. Bertsimas
Who trusts Allison Chang overall
- Cynthia Rudin
- Benjamin Letham
- Dmitry M. Malioutov
- Berk Ustun
- Kush R. Varshney
- Bishwamittra Ghosh
- Marc E. Pfetsch
- Ş. Ertekin
- Kuldeep S. Meel
- Sebastian Pokutta
Papers from Allison Chang's perspective
Ordered by how strongly the researchers Allison Chang trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Learning Multiple Layers of Features from Tiny Images
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
Their papers
- How to reverse-engineer quality rankings (2012) — 12 citations
- Integer optimization methods for machine learning (2012) — 7 citations
- ORC: Ordered Rules for ClassificationA Discrete Optimization Approach to Associative Classification (2012) — 15 citations
- An Integer Optimization Approach to Associative Classification (2012) — 22 citations