R. Chengalvarayan

1995–1998

A researcher in the Science corpus: 4 papers; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Whom R. Chengalvarayan trusts overall

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

1. Li Deng
2. Lawrence R. Rabiner
3. Shun-ichi Amari
4. Mari Ostendorf
5. Frederick Jelinek
6. Geoffrey E. Hinton
7. Dong Yu
8. Vassilios V. Digalakis
9. Yoshua Bengio
10. Abdel-rahman Mohamed

Who trusts R. Chengalvarayan overall

1. Li Deng
2. Dong Yu
3. Erik McDermott
4. Xiaodong He
5. Xiao Li
6. Timothy J. Hazen
7. Tony Jebara
8. Jonathan Le Roux

Papers from R. Chengalvarayan's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Long Short-Term Memory
4. Attention is All you Need (Neural Information Processing Systems)
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Gradient-based learning applied to document recognition
7. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
8. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (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

• Speech trajectory discrimination using the minimum classification error learning (1998)
• HMM-based speech recognition using state-dependent, discriminatively derived transforms on mel-warped DFT features (1997)
• Construction of state-dependent dynamic parameters using the maximum likelihood approach: Applications to speech recognition (1996)
• Use of generalized dynamic feature parameters for speech recognition: maximum likelihood and minimum classification error approaches (1995)