Luc Bégin

Artificial Intelligence · 2014–2016

A researcher in the Science corpus: 2 papers; trusts 8 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 20 citations into it
• Statistical Learning Theory — 18 citations into it
• Management Science and Operations Research — 8 citations into it
• Probabilistic & Bayesian Methods — 8 citations into it; #1,424 of 1,525 by trust here, #1,460 by citations

Whom Luc Bégin trusts overall

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

1. David A. McAllester
2. Yuhai Wu
3. Olivier Catoni
4. Arindam Banerjee
5. Pascal Germain
6. Yevgeny Seldin
7. John Shawe-Taylor
8. J. Langford
9. Matthias W. Seeger
10. François Laviolette

Who trusts Luc Bégin overall

1. Pierre Alquier
2. Pascal Germain
3. Wouter M. Kouw

Papers from Luc Bégin's perspective

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

1. PAC-Bayesian Stochastic Model Selection
2. Some PAC-Bayesian Theorems
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. PAC-Bayes & Margins
5. Statistical Learning Theory
6. Learning Multiple Layers of Features from Tiny Images
7. ImageNet classification with deep convolutional neural networks
8. Scikit-learn: Machine Learning in Python
9. Adaptive Subgradient Methods for Online Learning and Stochastic Optimization
10. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)

Their papers

• PAC-Bayesian Bounds based on the Rényi Divergence (2016) — 96 citations
• PAC-Bayesian Theory for Transductive Learning (2014) — 52 citations