Federico Girosi

Statistical Learning Theory · 1990–2005

A researcher in the Science corpus: 6 papers; trusts 9 researchers and is trusted by 87 researchers here, as inferred from the citation graph.

Subfields

• Statistical Learning Theory — 13 citations into it; #160 of 1,038 by trust here, #193 by citations
• Model Architectures — 5 citations into it; #237 of 2,278 by trust here, #585 by citations

Whom Federico Girosi trusts overall

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

1. Grace Wahba
2. Peter Craven
3. Vladimir Naumovich Vapni
4. Tomaso A. Poggio
5. Vladimir Naumovich Vapnik
6. Ingrid Daubechies
7. Michael J. Jones
8. C. Stone
9. Charles A. Micchelli
10. James Stewart

Who trusts Federico Girosi overall

1. Alex Smola
2. Bernhard Schölkopf
3. Volker Tresp
4. Tomaso A. Poggio
5. Ryan M. Rifkin
6. Johan A. K. Suykens
7. Serge J. Belongie
8. Jitendra Malik
9. Yoshua Bengio
10. Francis R. Bach

Papers from Federico Girosi's perspective

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

1. The Nature of Statistical Learning Theory
2. ImageNet classification with deep convolutional neural networks
3. Gradient-based learning applied to document recognition
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. Long Short-Term Memory
6. Linear Smoothers and Additive Models
7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet: A large-scale hierarchical image database
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Parallel and Deterministic Algorithms from MRFs: Surface Reconstruction (1991)
• Can electronic medical record systems transform health care? Potential health benefits, savings, and costs. (2005) — 1,851 citations
• An Equivalence Between Sparse Approximation and Support Vector Machines (1998)
• Regularization Theory and Neural Networks Architectures (1995)
• Networks for approximation and learning (1990)
• Regularization Algorithms for Learning That Are Equivalent to Multilayer Networks (1990)