Dimitrios Stamoulis
Computer Vision and Pattern Recognition · 2017–2019
A researcher in the Science corpus: 5 papers; trusts 233 researchers and is trusted by 8 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 83 citations into it; #9,067 of 21,575 by trust here, #7,176 by citations
- Artificial Intelligence — 77 citations into it; #14,694 of 35,345 by trust here, #11,327 by citations
- Efficiency & Compression — 39 citations into it; #746 of 1,264 by trust here, #644 by citations
- Model Architectures — 28 citations into it
- Neural Architecture Search & AutoML — 22 citations into it
- Optimization & Training — 17 citations into it
- Management Science and Operations Research — 7 citations into it
- ML Systems & Hardware — 6 citations into it; #341 of 575 by trust here, #464 by citations
Whom Dimitrios Stamoulis trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Krizhevsky
- Kaiming He
- Geoffrey E. Hinton
- Yoshua Bengio
- Barret Zoph
- Quoc V. Le
- Ross B. Girshick
- Karen Simonyan
- Yann LeCun
- Diederik P. Kingma
Who trusts Dimitrios Stamoulis overall
- Ruizhou Ding
- Xiangxiang Chu
- Lasse F. Wolff Anthony
- Hanhwi Jang
- Tien-Ju Yang
- Eva García-Martín
- Ting-Wu Chin
- Diana Marculescu
- Young Geun Kim
- Yingwei Li
Papers from Dimitrios Stamoulis's perspective
Ordered by how strongly the researchers Dimitrios Stamoulis 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
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
- Learning Multiple Layers of Features from Tiny Images
Their papers
- Single-Path NAS: Designing Hardware-Efficient ConvNets in less than 4 Hours (2019) — 291 citations
- Designing Adaptive Neural Networks for Energy-Constrained Image Classification (2018) — 67 citations
- Single-Path Mobile AutoML: Efficient ConvNet Design and NAS Hyperparameter Optimization (2019) — 37 citations
- HyperPower: Power- and memory-constrained hyper-parameter optimization for neural networks (2017) — 77 citations
- NeuralPower: Predict and Deploy Energy-Efficient Convolutional Neural Networks (2017) — 155 citations