Steffen Bickel

Artificial Intelligence · 2004–2012

A researcher in the Science corpus: 7 papers; trusts 33 researchers and is trusted by 103 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 30 citations into it; #2,431 of 35,345 by trust here, #4,298 by citations
• Statistics and Probability — 13 citations into it
• Probabilistic & Bayesian Methods — 12 citations into it
• Statistical Learning Theory — 11 citations into it
• Representation & Self-Supervised Learning — 10 citations into it; #562 of 3,145 by trust here, #755 by citations
• Computational Theory and Mathematics — 6 citations into it
• Computer Networks and Communications — 6 citations into it

Whom Steffen Bickel trusts overall

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

1. Bernard Walter Silverman
2. Lotfi A. Zadeh
3. Bianca Zadrozny
4. Iroon Polytechniou
5. James J. Heckman
6. Inderjit S. Dhillon
7. Kamal Nigam
8. Theodoros Evgeniou
9. Charles F. Manski
10. Arthur P. Dempster

Who trusts Steffen Bickel overall

1. Corinna Cortes
2. Masashi Sugiyama
3. Wouter M. Kouw
4. Qiang Yang
5. Mohammad Rostami
6. Mehryar Mohri
7. Bhavana Dalvi
8. Dacheng Tao
9. Virginia de Sa
10. John Blitzer

Papers from Steffen Bickel's perspective

Ordered by how strongly the researchers Steffen Bickel 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. Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper
6. Long Short-Term Memory
7. Attention is All you Need (Neural Information Processing Systems)
8. Reinforcement Learning: An Introduction
9. Learning Multiple Layers of Features from Tiny Images
10. ImageNet: A large-scale hierarchical image database

Their papers

• Discriminative Learning Under Covariate Shift (2009) — 443 citations
• Discriminative learning for differing training and test distributions (2007) — 486 citations
• Direct Density Ratio Estimation for Large-scale Covariate Shift Adaptation (2009) — 173 citations
• Multi-task learning for HIV therapy screening (2008) — 212 citations
• Multi-view clustering (2004) — 890 citations
• Machine Learning in Non-Stationary Environments - Introduction to Covariate Shift Adaptation (2012) — 434 citations
• Transfer Learning by Distribution Matching for Targeted Advertising (2008) — 39 citations