Jayanta Dey

Statistical Learning Theory · 2020–2021

A researcher in the Science corpus: 3 papers; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Statistical Learning Theory — 11 citations into it

Whom Jayanta Dey trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Vladimir Naumovich Vapnik
2. Gido M. van de Ven
3. Alex Krizhevsky
4. R. Caruana
5. Yann LeCun
6. Geoffrey E. Hinton
7. Leslie G. Valiant
8. Yali Amit

Papers from Jayanta Dey's perspective

Ordered by how strongly the researchers Jayanta Dey trusts endorse each paper. Same corpus, a different order for every researcher.

1. Gradient-based learning applied to document recognition
2. Attention is All you Need (Neural Information Processing Systems)
3. Learning Multiple Layers of Features from Tiny Images
4. ImageNet classification with deep convolutional neural networks
5. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
6. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
7. Long Short-Term Memory
8. Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation
9. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
10. Multitask Learning

Their papers

• Omnidirectional Transfer for Quasilinear Lifelong Learning (2021)
• Towards a theory of out-of-distribution learning (2021)
• A general approach to progressive learning (2020) — 10 citations