Panayotis Mertikopoulos
Artificial Intelligence · 2016–2021
A researcher in the Science corpus: 10 papers; trusts 70 researchers and is trusted by 15 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 93 citations into it; #11,189 of 35,345 by trust here, #12,974 by citations
- Optimization & Training — 87 citations into it; #1,665 of 2,601 by trust here, #1,335 by citations
- Computational Mechanics — 49 citations into it; #5,891 of 10,001 by trust here, #3,763 by citations
- Management Science and Operations Research — 45 citations into it; #4,076 of 11,946 by trust here, #2,957 by citations
- Computational Theory and Mathematics — 39 citations into it; #7,309 of 12,182 by trust here, #3,924 by citations
- Mathematical Optimization — 37 citations into it
- Numerical Analysis — 34 citations into it
- Computer Networks and Communications — 31 citations into it
Whom Panayotis Mertikopoulos trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Yurii E. Nesterov
- Shai Shalev-Shwartz
- Anatoli B. Juditsky
- Martin A. Zinkevich
- Lin Xiao
- L. Eon Bottou
- Elad Hazan
- Amir Beck
- Arkadi Nemirovski
- Nicolò Cesa-Bianchi
Who trusts Panayotis Mertikopoulos overall
- Zhengyuan Zhou
- Tianyi Lin
- Constantinos Daskalakis
- Nicolas Loizou
- Michael I. Jordan
- Noah Golowich
- Alina Ene
- Jelena Diakonikolas
- Yu-Guan Hsieh
- Chaobing Song
Papers from Panayotis Mertikopoulos's perspective
Ordered by how strongly the researchers Panayotis Mertikopoulos 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
- Learning Multiple Layers of Features from Tiny Images
- Attention is All you Need (Neural Information Processing Systems)
- 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
- Cycles in adversarial regularized learning (2017) — 365 citations
- Learning in games with continuous action sets and unknown payoff functions (2016) — 303 citations
- On the convergence of single-call stochastic extra-gradient methods (2019) — 189 citations
- Optimistic mirror descent in saddle-point problems: Going the extra (gradient) mile (2018) — 342 citations
- Finite-Time Last-Iterate Convergence for Multi-Agent Learning in Games (2020) — 59 citations
- Robust Power Management via Learning and Game Design (2021) — 30 citations
- Explore Aggressively, Update Conservatively: Stochastic Extragradient Methods with Variable Stepsize Scaling (2020) — 80 citations
- Distributed Asynchronous Optimization with Unbounded Delays: How Slow Can You Go? (2018) — 67 citations
- Mirror descent in saddle-point problems: Going the extra (gradient) mile (2018) — 33 citations
- Stochastic Mirror Descent in Variationally Coherent Optimization Problems (2017) — 88 citations