Theresa Ullmann

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 Theresa Ullmann trusts overall

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

1. Frank Hutter

Papers from Theresa Ullmann's perspective

Ordered by how strongly the researchers Theresa Ullmann 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. ImageNet classification with deep convolutional neural networks
5. Algorithms for Hyper-Parameter Optimization
6. Learning Multiple Layers of Features from Tiny Images
7. Gradient-based learning applied to document recognition
8. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
9. SGDR: Stochastic Gradient Descent with Warm Restarts
10. Sequential Model-Based Optimization for General Algorithm Configuration

Their papers

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