Jakub Marecek

Artificial Intelligence · 2010–2020

A researcher in the Science corpus: 5 papers; trusts 33 researchers and is trusted by 16 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 74 citations into it; #10,802 of 35,345 by trust here, #19,439 by citations
• Computational Theory and Mathematics — 26 citations into it
• Computational Mechanics — 20 citations into it; #2,552 of 10,001 by trust here, #4,749 by citations
• Atomic and Molecular Physics, and Optics — 19 citations into it
• Optimization & Training — 18 citations into it
• Numerical Analysis — 8 citations into it; #1,102 of 3,586 by trust here, #1,122 by citations
• Control and Systems Engineering — 7 citations into it
• Statistical Learning Theory — 5 citations into it

Whom Jakub Marecek trusts overall

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

1. Paul Tseng
2. Peter Richtárik
3. Yurii E. Nesterov
4. Olivier Fercoq
5. Martin Takác
6. B. Recht
7. Moritz Hardt
8. Elad Hazan
9. Shai Shalev-Shwartz
10. Sangwoon Yun

Who trusts Jakub Marecek overall

1. Jakub Konecný
2. Stephen J. Wright
3. Chenxin Ma
4. Biyi Fang
5. Xiangru Lian
6. Martin Takác
7. Steven S. Skiena
8. Peter Richtárik
9. Virginia Smith
10. Zhiqing Sun

Papers from Jakub Marecek's perspective

Ordered by how strongly the researchers Jakub Marecek 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. Learning Multiple Layers of Features from Tiny Images
7. ImageNet: A large-scale hierarchical image database
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Attention is All you Need (Neural Information Processing Systems)
10. Going deeper with convolutions

Their papers

• Distributed Block Coordinate Descent for Minimizing Partially Separable Functions (2014) — 64 citations
• Quantum Computing for Finance: State-of-the-Art and Future Prospects (2020) — 329 citations
• Warm-starting quantum optimization (2020) — 384 citations
• Robust Spectral Filtering and Anomaly Detection (2018)
• Handbook of Approximation Algorithms and Metaheuristics (2010) — 316 citations