Paul Ruvolo

Artificial Intelligence · 2008–2015

A researcher in the Science corpus: 7 papers; trusts 45 researchers and is trusted by 78 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 45 citations into it; #17,985 of 35,345 by trust here, #19,018 by citations
• Reinforcement Learning — 41 citations into it; #1,184 of 2,242 by trust here, #1,190 by citations
• Representation & Self-Supervised Learning — 13 citations into it; #388 of 3,145 by trust here, #939 by citations
• Computer Vision and Pattern Recognition — 8 citations into it; #11,365 of 21,575 by trust here, #16,367 by citations
• Optimization & Training — 7 citations into it
• Computational Theory and Mathematics — 6 citations into it
• Control and Systems Engineering — 5 citations into it

Whom Paul Ruvolo trusts overall

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

1. Jan Peters
2. Jian Zhang
3. Paul A. Viola
4. Richard S. Sutton
5. David Arthur
6. Ya Xue
7. Peter Buhlmann
8. Michail G. Lagoudakis
9. Ronald J. Williams
10. Zoubin Ghahramani

Who trusts Paul Ruvolo overall

1. Bing Liu
2. Jorge Armando Mendez Mendez
3. Mohammad Rostami
4. Eric Eaton
5. Anastasia Pentina
6. Haitham Bou-Ammar
7. Gan Sun
8. Zixuan Ke
9. David Isele
10. Zhiyuan Chen

Papers from Paul Ruvolo's perspective

Ordered by how strongly the researchers Paul Ruvolo 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. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
7. Attention is All you Need (Neural Information Processing Systems)
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Learning Multiple Layers of Features from Tiny Images
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Active Task Selection for Lifelong Machine Learning (2013) — 77 citations
• Unsupervised Cross-Domain Transfer in Policy Gradient Reinforcement Learning via Manifold Alignment (2015) — 96 citations
• Autonomous Cross-Domain Knowledge Transfer in Lifelong Policy Gradient Reinforcement Learning (2015) — 81 citations
• Online Multi-Task Learning for Policy Gradient Methods (2014) — 175 citations
• ELLA: An Efficient Lifelong Learning Algorithm (2013) — 394 citations
• Whose Vote Should Count More: Optimal Integration of Labels from Labelers of Unknown Expertise (2009) — 1,336 citations
• Optimization on a Budget: A Reinforcement Learning Approach (2008) — 15 citations