Zhengyuan Zhou
Artificial Intelligence · 2012–2021
A researcher in the Science corpus: 15 papers; trusts 281 researchers and is trusted by 27 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 143 citations into it; #9,855 of 35,345 by trust here, #6,664 by citations
- Management Science and Operations Research — 77 citations into it; #4,436 of 11,946 by trust here, #5,787 by citations
- Optimization & Training — 70 citations into it; #1,286 of 2,601 by trust here, #560 by citations
- Statistics and Probability — 69 citations into it
- Computer Vision and Pattern Recognition — 51 citations into it; #8,323 of 21,575 by trust here, #4,834 by citations
- Computational Mechanics — 42 citations into it
- Reinforcement Learning — 33 citations into it; #1,342 of 2,242 by trust here, #1,844 by citations
- Computer Networks and Communications — 31 citations into it
Whom Zhengyuan Zhou trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Yurii E. Nesterov
- Alex Krizhevsky
- Geoffrey E. Hinton
- Susan Athey
- Yoshua Bengio
- Kaiming He
- Donald B. Rubin
- Shai Shalev-Shwartz
- Christian Szegedy
- Ilya Sutskever
Who trusts Zhengyuan Zhou overall
- Maximilian Hüttenrauch
- Tianyi Lin
- Nicolas Loizou
- Susan Athey
- Panayotis Mertikopoulos
- Lu Jiang
- Chaobing Song
- Adrian Šošić
- Fahad Sarfraz
- Bo Han
Papers from Zhengyuan Zhou's perspective
Ordered by how strongly the researchers Zhengyuan Zhou trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- Learning Multiple Layers of Features from Tiny Images
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- MentorNet: Learning Data-Driven Curriculum for Very Deep Neural Networks on Corrupted Labels (2017) — 1,683 citations
- MentorNet: Regularizing Very Deep Neural Networks on Corrupted Labels (2017) — 83 citations
- Learning in games with continuous action sets and unknown payoff functions (2016) — 303 citations
- Optimistic Dual Extrapolation for Coherent Non-monotone Variational Inequalities (2021) — 54 citations
- Offline Multi-Action Policy Learning: Generalization and Optimization (2018) — 152 citations
- Finite-Time Last-Iterate Convergence for Multi-Agent Learning in Games (2020) — 59 citations
- A general, open-loop formulation for reach-avoid games (2012) — 77 citations
- Robust Power Management via Learning and Game Design (2021) — 30 citations
- Balanced Linear Contextual Bandits (2018) — 77 citations
- Distributed Asynchronous Optimization with Unbounded Delays: How Slow Can You Go? (2018) — 67 citations
- Stochastic Mirror Descent in Variationally Coherent Optimization Problems (2017) — 88 citations
- Cooperative pursuit with Voronoi partitions (2016) — 207 citations
- Multiplayer Reach-Avoid Games via Pairwise Outcomes (2016) — 172 citations
- Multiplayer reach-avoid games via low dimensional solutions and maximum matching (2014) — 73 citations
- A path defense approach to the multiplayer reach-avoid game (2014) — 60 citations