Gayatree Ganu
Artificial Intelligence · 2009–2013
A researcher in the Science corpus: 2 papers; trusts 19 researchers and is trusted by 3 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 13 citations into it; #27,950 of 35,345 by trust here, #29,412 by citations
- Information Systems — 13 citations into it; #6,451 of 8,771 by trust here, #7,107 by citations
- Recommender Systems — 7 citations into it
- Management Science and Operations Research — 5 citations into it
Whom Gayatree Ganu trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Thorsten Joachims
- Paul Resnick
- Ron Kohavi
- Yehuda Koren
- Noam Slonim
- Jonathan L. Herlocker
- Naftali Tishby
- J. Breese
- Chong Wang
- Ana-Maria Popescu
Who trusts Gayatree Ganu overall
- Maria Pontiki
- Julian McAuley
- Wayne Xin Zhao
- Li Chen
- Alireza Alaei
- Ruidan He
- Dimitris Galanis
- Seungyeon Kim
- Jure Leskovec
- Qingshan Jiang
Papers from Gayatree Ganu's perspective
Ordered by how strongly the researchers Gayatree Ganu 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)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- 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)
- Learning Multiple Layers of Features from Tiny Images
- Latent Dirichlet Allocation
Their papers
- Improving the quality of predictions using textual information in online user reviews (2013) — 157 citations
- Beyond the Stars: Improving Rating Predictions using Review Text Content (2009) — 492 citations