Vijay Arya
Artificial Intelligence · 2001–2019
A researcher in the Science corpus: 5 papers; trusts 25 researchers and is trusted by 5 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 62 citations into it; #31,720 of 35,345 by trust here, #15,542 by citations
- Safety, Robustness & Interpretability — 38 citations into it
- Organizational Behavior and Human Resource Management — 8 citations into it; #4,908 of 8,741 by trust here, #4,293 by citations
- Industrial and Manufacturing Engineering — 7 citations into it; #1,107 of 2,521 by trust here, #896 by citations
- Computational Theory and Mathematics — 6 citations into it
- Information Systems — 5 citations into it
Whom Vijay Arya trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Kamal Kumar Jain
- Sudipto Guha
- Geoffrey E. Hinton
- Vijay V. Vazirani
- Moses Charikar
- Ilya Sutskever
- Oriol Vinyals
- Yoshua Bengio
- Alex Krizhevsky
- Madhukar R. Korupolu
Who trusts Vijay Arya overall
- Kamal Kumar Jain
- Adam Meyerson
- Mohammad Mahdian
- Clemens Rösner
- Amin Saberi
- Xingyu Chen
- Flavio Chierichetti
- Gesina Schwalbe
- Jaroslaw Byrka
- Franziska Boenisch
Papers from Vijay Arya's perspective
Ordered by how strongly the researchers Vijay Arya 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
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- Learning Multiple Layers of Features from Tiny Images
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- Model Extraction Warning in MLaaS Paradigm (2017) — 161 citations
- Fair Transfer of Multiple Style Attributes in Text (2019)
- One Explanation Does Not Fit All: A Toolkit and Taxonomy of AI Explainability Techniques (2019) — 478 citations
- Local Search Heuristics for k-Median and Facility Location Problems (2004) — 698 citations
- Local search heuristic for k-median and facility location problems (2001) — 391 citations