Networks for approximation and learning T Poggio, F Girosi Proceedings of the IEEE 78 (9), 1481-1497, 1990 | 4224 | 1990 |

Training support vector machines: an application to face detection E Osuna, R Freund, F Girosi cvpr 97 (130-136), 99, 1997 | 3439 | 1997 |

Can electronic medical record systems transform health care? Potential health benefits, savings, and costs R Hillestad, J Bigelow, A Bower, F Girosi, R Meili, R Scoville, R Taylor Health affairs 24 (5), 1103-1117, 2005 | 1911 | 2005 |

An improved training algorithm for support vector machines E Osuna, R Freund, F Girosi Neural networks for signal processing VII. Proceedings of the 1997 IEEE …, 1997 | 1586 | 1997 |

Regularization theory and neural networks architectures F Girosi, M Jones, T Poggio Neural computation 7 (2), 219-269, 1995 | 1517 | 1995 |

Comparing support vector machines with Gaussian kernels to radial basis function classifiers B Scholkopf, KK Sung, CJC Burges, F Girosi, P Niyogi, T Poggio, ... IEEE transactions on Signal Processing 45 (11), 2758-2765, 1997 | 1346 | 1997 |

Regularization algorithms for learning that are equivalent to multilayer networks T Poggio, F Girosi Science 247 (4945), 978-982, 1990 | 1295 | 1990 |

Regularization algorithms for learning that are equivalent to multilayer networks T Poggio, F Girosi Science 247 (4945), 978-982, 1990 | 1295 | 1990 |

Support vector machines: Training and applications EE Osuna Massachusetts Institute of Technology, 1998 | 1038 | 1998 |

Networks and the best approximation property F Girosi, T Poggio Biological cybernetics 63 (3), 169-176, 1990 | 1016 | 1990 |

A theory of networks for approximation and learning T Poggio, F Girosi MASSACHUSETTS INST OF TECH CAMBRIDGE ARTIFICIAL INTELLIGENCE LAB, 1989 | 945 | 1989 |

A theory of networks for approximation and learning T Poggio, F Girosi MASSACHUSETTS INST OF TECH CAMBRIDGE ARTIFICIAL INTELLIGENCE LAB, 1989 | 934 | 1989 |

Nonlinear prediction of chaotic time series using support vector machines S Mukherjee, E Osuna, F Girosi Neural Networks for Signal Processing VII. Proceedings of the 1997 IEEE …, 1997 | 704 | 1997 |

An equivalence between sparse approximation and support vector machines F Girosi Neural computation 10 (6), 1455-1480, 1998 | 678 | 1998 |

Parallel and deterministic algorithms from MRFs: Surface reconstruction D Geiger, F Girosi IEEE Transactions on Pattern Analysis & Machine Intelligence, 401-412, 1991 | 647 | 1991 |

A computational approach to motion perception S Uras, F Girosi, A Verri, V Torre Biological Cybernetics 60 (2), 79-87, 1988 | 512 | 1988 |

Reducing the global burden of tuberculosis: the contribution of improved diagnostics E Keeler, MD Perkins, P Small, C Hanson, S Reed, J Cunningham, ... Nature 444 (1s), 49, 2006 | 304 | 2006 |

Incorporating prior information in machine learning by creating virtual examples P Niyogi, F Girosi, T Poggio Proceedings of the IEEE 86 (11), 2196-2209, 1998 | 301 | 1998 |

Reducing the run-time complexity of support vector machines E Osuna, F Girosi International Conference on Pattern Recognition (submitted), 1998 | 237 | 1998 |

On the relationship between generalization error, hypothesis complexity, and sample complexity for radial basis functions P Niyogi, F Girosi Neural Computation 8 (4), 819-842, 1996 | 234 | 1996 |