Horia Mania

Artificial Intelligence · 2015–2020

A researcher in the Science corpus: 8 papers; trusts 137 researchers and is trusted by 19 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 132 citations into it; #14,784 of 35,345 by trust here, #7,858 by citations
• Computer Vision and Pattern Recognition — 57 citations into it
• Reinforcement Learning — 52 citations into it; #1,185 of 2,242 by trust here, #926 by citations
• Optimization & Training — 46 citations into it; #1,457 of 2,601 by trust here, #812 by citations
• Computational Mechanics — 25 citations into it; #3,245 of 10,001 by trust here, #1,325 by citations
• Computational Theory and Mathematics — 21 citations into it; #8,508 of 12,182 by trust here, #2,761 by citations
• Control and Systems Engineering — 21 citations into it; #2,413 of 8,257 by trust here, #1,814 by citations
• Management Science and Operations Research — 19 citations into it; #6,718 of 11,946 by trust here, #2,355 by citations

Whom Horia Mania trusts overall

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

1. John Schulman
2. Geoffrey E. Hinton
3. Alex Krizhevsky
4. Sergey Levine
5. Sham M. Kakade
6. Diederik P. Kingma
7. Yoshua Bengio
8. Richard S. Sutton
9. Ilya Sutskever
10. Yurii E. Nesterov

Who trusts Horia Mania overall

1. Sebastian U. Stich
2. B. Recht
3. Wen Sun
4. Rémi Leblond
5. Sarah Dean
6. Fabian Pedregosa
7. Lam M. Nguyen
8. Thomas Liao
9. Hao Yu
10. Jack Parker-Holder

Papers from Horia Mania's perspective

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

Their papers

• Simple random search provides a competitive approach to reinforcement learning (2018) — 338 citations
• Evaluating Machine Accuracy on ImageNet (2020) — 158 citations
• Perturbed Iterate Analysis for Asynchronous Stochastic Optimization (2015) — 252 citations
• Learning Without Mixing: Towards A Sharp Analysis of Linear System Identification (2018) — 388 citations
• Regret Bounds for Robust Adaptive Control of the Linear Quadratic Regulator (2018) — 304 citations
• Model Similarity Mitigates Test Set Overuse (2019) — 61 citations
• Simple random search of static linear policies is competitive for reinforcement learning (2018) — 309 citations
• On the Sample Complexity of the Linear Quadratic Regulator (2017) — 642 citations