Horst Samulowitz
Artificial Intelligence · 2007–2019
A researcher in the Science corpus: 7 papers; trusts 45 researchers and is trusted by 15 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 53 citations into it; #9,883 of 35,345 by trust here, #13,760 by citations
- Computer Vision and Pattern Recognition — 31 citations into it
- Neural Architecture Search & AutoML — 13 citations into it
- Optimization & Training — 12 citations into it
- Information Systems — 11 citations into it
- Computational Theory and Mathematics — 10 citations into it
- Management Science and Operations Research — 10 citations into it; #5,377 of 11,946 by trust here, #6,888 by citations
- Computer Networks and Communications — 9 citations into it
Whom Horst Samulowitz trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Eric R. Ziegel
- Armin Biere
- Yoshua Bengio
- Geoffrey E. Hinton
- Michail G. Lagoudakis
- James Bergstra
- Alex Krizhevsky
- Shaul Markovitch
- Ofer Dor
- Karen Simonyan
Who trusts Horst Samulowitz overall
- Elias Boutros Khalil
- Lars Kotthoff
- Marc-André Zöller
- Yuri Malitsky
- K. Smith‐Miles
- Lin Xu
- Mustafa Misir
- Frank Hutter
- Marco F. Huber
- Gang Luo
Papers from Horst Samulowitz's perspective
Ordered by how strongly the researchers Horst Samulowitz 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
- Attention is All you Need (Neural Information Processing Systems)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Learning Multiple Layers of Features from Tiny Images
- ImageNet: A large-scale hierarchical image database
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Selecting Near-Optimal Learners via Incremental Data Allocation (2015) — 66 citations
- Guiding Combinatorial Optimization with UCT (2012) — 82 citations
- Human-AI Collaboration in Data Science (2019) — 338 citations
- Learning Feature Engineering for Classification (2017) — 300 citations
- Feature Engineering for Predictive Modeling using Reinforcement Learning (2017) — 237 citations
- Image inpainting through neural networks hallucinations (2016) — 31 citations
- Learning to Solve QBF (2007) — 100 citations