Olga Papaemmanouil

Artificial Intelligence · 2016–2019

A researcher in the Science corpus: 2 papers; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 27 citations into it
• Reinforcement Learning — 6 citations into it

Whom Olga Papaemmanouil trusts overall

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

1. Manas R. Joglekar
2. Tian Zhang
3. David Cohn
4. Hector Garcia-Molina
5. Raghu Ramakrishnan
6. Leo Breiman

Papers from Olga Papaemmanouil's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. Layer Normalization
4. Efficient Estimation of Word Representations in Vector Space
5. Human-level control through deep reinforcement learning
6. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
7. Fully convolutional networks for semantic segmentation
8. Visualizing Data using t-SNE
9. Attention is All you Need (Neural Information Processing Systems)
10. Gradient-based learning applied to document recognition

Their papers

• Neo: A Learned Query Optimizer (2019) — 518 citations
• Interactive Data Exploration via Machine Learning Models (2016) — 22 citations