Pararth Shah

Artificial Intelligence · 2016–2019

A researcher in the Science corpus: 8 papers; trusts 136 researchers and is trusted by 22 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 133 citations into it; #9,059 of 35,345 by trust here, #7,172 by citations
• Natural Language Processing — 84 citations into it; #1,930 of 5,688 by trust here, #1,721 by citations
• Computer Vision and Pattern Recognition — 37 citations into it
• Reinforcement Learning — 37 citations into it; #1,443 of 2,242 by trust here, #1,163 by citations
• Representation & Self-Supervised Learning — 10 citations into it
• Management Science and Operations Research — 8 citations into it
• Optimization & Training — 5 citations into it

Whom Pararth Shah trusts overall

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

1. Ronald J. Williams
2. Antoine Bordes
3. Geoffrey E. Hinton
4. Diederik P. Kingma
5. Yoshua Bengio
6. Jason Aaron Edward Weston
7. Ilya Sutskever
8. Pei-hao Su
9. Alex Krizhevsky
10. Alex Graves

Who trusts Pararth Shah overall

1. Stephen Roller
2. Seungwhan Moon
3. Abhinav Rastogi
4. Bing Liu
5. Dilek Z. Hakkani-Tür
6. Andrea Madotto
7. Chien-Sheng Wu
8. Gökhan Tür
9. Y-Lan Boureau
10. Milan Gritta

Papers from Pararth Shah's perspective

Ordered by how strongly the researchers Pararth Shah 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. ImageNet classification with deep convolutional neural networks
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. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
9. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
10. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)

Their papers

• Dialogue Learning with Human Teaching and Feedback in End-to-End Trainable Task-Oriented Dialogue Systems (2018) — 176 citations
• OpenDialKG: Explainable Conversational Reasoning with Attention-based Walks over Knowledge Graphs (2019) — 346 citations
• Bootstrapping a Neural Conversational Agent with Dialogue Self-Play, Crowdsourcing and On-Line Reinforcement Learning (2018) — 151 citations
• Building a Conversational Agent Overnight with Dialogue Self-Play (2018) — 208 citations
• Memory Grounded Conversational Reasoning (2019) — 5 citations
• Recommendation as a Communication Game: Self-Supervised Bot-Play for Goal-oriented Dialogue (2019) — 125 citations
• Federated Control with Hierarchical Multi-Agent Deep Reinforcement Learning (2017) — 36 citations
• Interactive reinforcement learning for task-oriented dialogue management (2016) — 54 citations