### Abstract

The class of logconcave functions in ℝ^{n} is a common generalization of Gaussians and of indicator functions of convex sets. Motivated by the problem of sampling from a logconcave density function, we study their geometry and introduce an analysis technique for "smoothing" them out. This leads to efficient sampling algorithms with no assumptions on the local smoothness of the density function. After appropriate preprocessing, both the ball walk (with a Metropolis filter) and a generalization of hit-and-run produce a point from approximately the right distribution in time O∗(n^{4}), and in amortized time O∗(n^{3}) if many sample points are needed (where the asterisk indicates that dependence on the error parameter and factors of log n are not shown). The bounds are optimal in terms of a "roundness" parameter and match the best-known bounds for the special case of the uniform density over a convex set.

Original language | English |
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Title of host publication | Proceedings - 44th Annual IEEE Symposium on Foundations of Computer Science, FOCS 2003 |

Publisher | IEEE Computer Society |

Pages | 640-649 |

Number of pages | 10 |

ISBN (Electronic) | 0769520405 |

DOIs | |

Publication status | Published - Jan 1 2003 |

Event | 44th Annual IEEE Symposium on Foundations of Computer Science, FOCS 2003 - Cambridge, United States Duration: Oct 11 2003 → Oct 14 2003 |

### Publication series

Name | Proceedings - Annual IEEE Symposium on Foundations of Computer Science, FOCS |
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Volume | 2003-January |

ISSN (Print) | 0272-5428 |

### Other

Other | 44th Annual IEEE Symposium on Foundations of Computer Science, FOCS 2003 |
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Country | United States |

City | Cambridge |

Period | 10/11/03 → 10/14/03 |

### Fingerprint

### Keywords

- Density functional theory
- Engineering profession
- Filters
- Gaussian processes
- Geometry
- Lattices
- Mathematics
- Probability distribution
- Sampling methods
- Stochastic processes

### ASJC Scopus subject areas

- Computer Science(all)

### Cite this

*Proceedings - 44th Annual IEEE Symposium on Foundations of Computer Science, FOCS 2003*(pp. 640-649). [1238236] (Proceedings - Annual IEEE Symposium on Foundations of Computer Science, FOCS; Vol. 2003-January). IEEE Computer Society. https://doi.org/10.1109/SFCS.2003.1238236