Marc Becker

Artificial Intelligence · 2021

A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 92 citations into it
• Computational Theory and Mathematics — 35 citations into it
• Optimization & Training — 32 citations into it
• Neural Architecture Search & AutoML — 16 citations into it

Whom Marc Becker trusts overall

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

1. Frank Hutter

Papers from Marc Becker's perspective

Ordered by how strongly the researchers Marc Becker trusts endorse each paper. Same corpus, a different order for every researcher.

1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
2. Practical Bayesian Optimization of Machine Learning Algorithms
3. Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
4. Algorithms for Hyper-Parameter Optimization
5. ImageNet classification with deep convolutional neural networks
6. Sequential Model-Based Optimization for General Algorithm Configuration
7. SGDR: Stochastic Gradient Descent with Warm Restarts
8. Scalable Bayesian Optimization Using Deep Neural Networks
9. Learning Multiple Layers of Features from Tiny Images
10. Gradient-based learning applied to document recognition

Their papers

• Hyperparameter optimization: Foundations, algorithms, best practices, and open challenges (2021) — 1,013 citations