Isabella Lukasewitz
Optimization & Training · 2016
A researcher in the Science corpus: 1 paper; trusts 41 researchers and is trusted by 4 researchers here, as inferred from the citation graph.
Subfields
- Optimization & Training — 28 citations into it; #2,179 of 2,601 by trust here, #1,841 by citations
- Artificial Intelligence — 20 citations into it; #27,071 of 35,345 by trust here, #21,316 by citations
- Computer Vision and Pattern Recognition — 17 citations into it; #15,463 of 21,575 by trust here, #14,151 by citations
- Computational Mechanics — 12 citations into it
- Natural Language Processing — 7 citations into it
- Statistical Learning Theory — 6 citations into it
- Numerical Analysis — 5 citations into it
Whom Isabella Lukasewitz trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Martin Jaggi
- Yurii E. Nesterov
- Simon Lacoste-Julien
- Thorsten Joachims
- Pedro F. Felzenszwalb
- Trevor J. Hastie
- Geoffrey E. Hinton
- Robert Tibshirani
- David G. Lowe
- Charles A. Holloway
Who trusts Isabella Lukasewitz overall
Papers from Isabella Lukasewitz's perspective
Ordered by how strongly the researchers Isabella Lukasewitz 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)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- 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 Large Scale Visual Recognition Challenge
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Distinctive Image Features from Scale-Invariant Keypoints
Their papers
- Minding the Gaps for Block Frank-Wolfe Optimization of Structured SVMs (2016) — 70 citations