Sahisnu Mazumder

Artificial Intelligence · 2018–2022

A researcher in the Science corpus: 10 papers; trusts 303 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 236 citations into it; #16,300 of 35,345 by trust here, #16,771 by citations
• Natural Language Processing — 163 citations into it
• Computer Vision and Pattern Recognition — 70 citations into it
• Reinforcement Learning — 42 citations into it
• Meta & Continual Learning — 35 citations into it; #752 of 1,041 by trust here, #963 by citations
• Representation & Self-Supervised Learning — 34 citations into it
• Information Systems — 26 citations into it
• Graph Learning — 12 citations into it

Whom Sahisnu Mazumder trusts overall

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

1. Bing Liu
2. Diederik P. Kingma
3. Yoshua Bengio
4. Geoffrey E. Hinton
5. Antoine Bordes
6. Jason Aaron Edward Weston
7. Ilya Sutskever
8. Tomas Mikolov
9. Sepp Hochreiter
10. Luke S. Zettlemoyer

Who trusts Sahisnu Mazumder overall

1. Bing Liu
2. Zixuan Ke
3. Eric Robertson
4. Kurt Shuster
5. Scott Grigsby
6. C. Mei
7. Shuai Wang
8. Jack Urbanek
9. Nianzu Ma
10. Gyuhak Kim

Papers from Sahisnu Mazumder's perspective

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

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
9. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
10. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers

• Towards a Continuous Knowledge Learning Engine for Chatbots (2018) — 23 citations
• FLIN: A Flexible Natural Language Interface for Web Navigation (2020) — 29 citations
• Lifelong and Continual Learning Dialogue Systems: Learning during Conversation (2021) — 51 citations
• AI Autonomy: Self-initiated Open-world Continual Learning and Adaptation (2022) — 49 citations
• Self-Initiated Open World Learning for Autonomous AI Agents (2021) — 11 citations
• An Application-Independent Approach to Building Task-Oriented Chatbots with Interactive Continual Learning (2020)
• Lifelong Learning Dialogue Systems: Chatbots that Self-Learn On the Job (2020) — 5 citations
• Continuous and Interactive Factual Knowledge Learning in Verification Dialogues (2020)
• Lifelong and Interactive Learning of Factual Knowledge in Dialogues (2019) — 28 citations
• Lifelong Learning Memory Networks for Aspect Sentiment Classification (2018) — 30 citations