Mona Eberts

Statistical Learning Theory · 2013–2015

A researcher in the Science corpus: 2 papers; trusts 12 researchers and is trusted by 8 researchers here, as inferred from the citation graph.

Subfields

• Statistical Learning Theory — 10 citations into it
• Statistics and Probability — 10 citations into it; #5,738 of 12,932 by trust here, #10,275 by citations
• Artificial Intelligence — 9 citations into it; #15,791 of 35,345 by trust here, #26,682 by citations
• Mathematical Physics — 5 citations into it

Whom Mona Eberts trusts overall

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

1. Ingo Steinwart
2. Steve Smale
3. Felipe Cucker
4. Shahar Mendelson
5. Youjuan Li
6. Andreas Christmann
7. Ding-Xuan Zhou
8. Ichiro Takeuchi
9. Joe Neeman
10. Clint Scovel

Who trusts Mona Eberts overall

1. Motonobu Kanagawa
2. Yichi Zhang
3. Yu Nishiyama
4. Kenji Fukumizu
5. Eric B. Laber
6. Arthur Gretton
7. Marie Davidian

Papers from Mona Eberts's perspective

Ordered by how strongly the researchers Mona Eberts 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. Gradient-based learning applied to document recognition
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Spline Models for Observational Data
6. Long Short-Term Memory
7. Attention is All you Need (Neural Information Processing Systems)
8. Support vector machines
9. Learning Multiple Layers of Features from Tiny Images
10. ImageNet: A large-scale hierarchical image database

Their papers

• Safe Exploration for Active Learning with Gaussian Processes (2015) — 116 citations
• Optimal regression rates for SVMs using Gaussian kernels (2013) — 87 citations