Alp Yurtsever
Computational Mechanics · 2001–2018
A researcher in the Science corpus: 4 papers; trusts 41 researchers and is trusted by 14 researchers here, as inferred from the citation graph.
Subfields
- Computational Mechanics — 32 citations into it; #3,138 of 10,001 by trust here, #5,567 by citations
- Artificial Intelligence — 29 citations into it; #12,730 of 35,345 by trust here, #23,077 by citations
- Optimization & Training — 29 citations into it; #1,322 of 2,601 by trust here, #2,081 by citations
- Numerical Analysis — 12 citations into it; #1,879 of 3,586 by trust here, #1,831 by citations
- Mathematical Optimization — 10 citations into it
- Computer Vision and Pattern Recognition — 9 citations into it
- Computational Theory and Mathematics — 8 citations into it
- Management Science and Operations Research — 7 citations into it; #5,243 of 11,946 by trust here, #9,383 by citations
Whom Alp Yurtsever trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Yurii E. Nesterov
- Martin Jaggi
- E.J. Candes
- Kenneth L. Clarkson
- R. Tyrrell Rockafellar
- Michael W. Mahoney
- David P. Woodruff
- Long Chen
- Anatoli B. Juditsky
- Shai Shalev-Shwartz
Who trusts Alp Yurtsever overall
- Tom Goldstein
- Gauthier Gidel
- Kfir Yehuda Levy
- Fangyu Zou
- Xiaoyun Li
- Christoph Studer
- Yuege Xie
- Fabian Pedregosa
- Simon Lacoste-Julien
Papers from Alp Yurtsever's perspective
Ordered by how strongly the researchers Alp Yurtsever trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Gradient-based learning applied to document recognition
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Adaptive Subgradient Methods for Online Learning and Stochastic Optimization
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Learning Multiple Layers of Features from Tiny Images
Their papers
- A Universal Primal-Dual Convex Optimization Framework (2015) — 63 citations
- Online Adaptive Methods, Universality and Acceleration (2018) — 110 citations
- Sketchy Decisions: Convex Low-Rank Matrix Optimization with Optimal Storage (2017) — 100 citations
- On a nonlocal boundary value problem for semilinear hyperbolic-parabolic equations (2001) — 50 citations