Shaileshh Bojja Venkatakrishnan

Artificial Intelligence · 2018

A researcher in the Science corpus: 1 paper; trusts 13 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 29 citations into it
• Reinforcement Learning — 20 citations into it
• Computer Vision and Pattern Recognition — 10 citations into it
• Optimization & Training — 5 citations into it

Whom Shaileshh Bojja Venkatakrishnan trusts overall

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

1. Ronald J. Williams
2. Richard S. Sutton
3. Radford M. Neal
4. Hongzi Mao
5. Geoffrey E. Hinton
6. Pieter Abbeel
7. Diederik P. Kingma
8. Andrew Barto
9. Yoshua Bengio
10. John Schulman

Papers from Shaileshh Bojja Venkatakrishnan's perspective

Ordered by how strongly the researchers Shaileshh Bojja Venkatakrishnan 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Human-level control through deep reinforcement learning
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. Attention is All you Need (Neural Information Processing Systems)
8. Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning
9. ImageNet: A large-scale hierarchical image database
10. Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks

Their papers

• Learning scheduling algorithms for data processing clusters (2018) — 812 citations