George Ke

Artificial Intelligence · 2016

A researcher in the Science corpus: 1 paper; trusts 9 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 8 citations into it
• Computational Theory and Mathematics — 6 citations into it
• Optimization & Training — 6 citations into it

Whom George Ke trusts overall

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

1. James Bergstra
2. Jasper Snoek
3. Katharina Eggensperger

Papers from George Ke's perspective

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

1. Practical Bayesian Optimization of Machine Learning Algorithms
2. Random Search for Hyper-Parameter Optimization
3. Algorithms for Hyper-Parameter Optimization
4. Sequential Model-Based Optimization for General Algorithm Configuration
5. Scalable Bayesian Optimization Using Deep Neural Networks
6. Input Warping for Bayesian Optimization of Non-Stationary Functions
7. Towards an Empirical Foundation for Assessing Bayesian Optimization of Hyperparameters
8. Statistical Comparisons of Classifiers over Multiple Data Sets
9. ImageNet classification with deep convolutional neural networks
10. Efficient Benchmarking of Hyperparameter Optimizers via Surrogates

Their papers

• A Stratified Analysis of Bayesian Optimization Methods (2016) — 39 citations