Nashid Shahriar

Computer Networks and Communications · 2018

A researcher in the Science corpus: 1 paper; trusts 15 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Networks and Communications — 62 citations into it
• Artificial Intelligence — 58 citations into it
• Computer Vision and Pattern Recognition — 12 citations into it
• Electrical and Electronic Engineering — 12 citations into it
• Probabilistic & Bayesian Methods — 10 citations into it
• Statistical Learning Theory — 9 citations into it
• Model Architectures — 9 citations into it
• Reinforcement Learning — 8 citations into it

Whom Nashid Shahriar trusts overall

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

1. Geoffrey E. Hinton
2. Jerome H. Friedman
3. Richard S. Sutton
4. Robert Tibshirani
5. David H. Hubel
6. Yoshua Bengio
7. Teuvo Kohonen
8. David E. Rumelhart
9. J. Ross Quinlan

Papers from Nashid Shahriar's perspective

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

1. Long Short-Term Memory
2. ImageNet classification with deep convolutional neural networks
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Gradient-based learning applied to document recognition
5. Human-level control through deep reinforcement learning
6. A Fast Learning Algorithm for Deep Belief Nets
7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
8. Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper
9. Attention is All you Need (Neural Information Processing Systems)
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• A comprehensive survey on machine learning for networking: evolution, applications and research opportunities (2018) — 955 citations