M. McCourt

Artificial Intelligence · 2015–2021

A researcher in the Science corpus: 4 papers; trusts 18 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 46 citations into it; #33,696 of 35,345 by trust here, #21,316 by citations
• Computational Theory and Mathematics — 31 citations into it; #11,603 of 12,182 by trust here, #6,463 by citations
• Optimization & Training — 19 citations into it; #2,524 of 2,601 by trust here, #2,259 by citations
• Neural Architecture Search & AutoML — 7 citations into it

Whom M. McCourt trusts overall

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

1. James Bergstra
2. Jasper Snoek
3. Frank Hutter
4. Katharina Eggensperger
5. Yoshua Bengio
6. Geoffrey E. Hinton
7. Nikolaus Hansen
8. Hugo Larochelle
9. Peter I. Frazier
10. Alex Krizhevsky

Who trusts M. McCourt overall

1. Sakorn Mekruksavanich
2. Shuhei Watanabe
3. Andrés Camero

Papers from M. McCourt's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. Learning Multiple Layers of Features from Tiny Images
6. Attention is All you Need (Neural Information Processing Systems)
7. Long Short-Term Memory
8. ImageNet: A large-scale hierarchical image database
9. Going deeper with convolutions
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• A Stratified Analysis of Bayesian Optimization Methods (2016) — 39 citations
• Bayesian Optimization is Superior to Random Search for Machine Learning Hyperparameter Tuning: Analysis of the Black-Box Optimization Challenge 2020 (2021) — 404 citations
• Bayesian Optimization over Sets (2019) — 9 citations
• Kernel-based Approximation Methods using MATLAB (2015) — 376 citations