2016年度 第1回データ科学 ミニレクチャーシリーズ（CREST JST 共催）
Introduction to Sequential Monte Carlo Methods and Multilevel Sequential Monte Carlo
Ajay Jasra (National University of Singapore)
7/5（火） 13:00~14:30 Mini-Lecture 1/3
7/12（火） 13:00~14:30 Mini-Lecture 2/3
7/19（火） 13:00~14:30 Mini-Lecture 3/3
This course will provide a tutorial style introduction to sequential Monte Carlo methods, attempting to start from a basic introduction, to a coverage of some of the latest research developments.
Sequential Monte Carlo methods are applied in a wide variety of applications, including engineering, economics and biology. They combine importance sampling and resampling to approximate distributions. The idea is to introduce a sequence of proposal densities and sequentially simulate a collection of N >1 samples, termed particles, in parallel from these proposals. In most scenarios it is not possible to use the distribution of interest as a proposal.
Therefore, one must correct for the discrepancy between proposal and target via importance weights. There are a variety of algorithms and extensions which form some of the most cutting edge methodology for `exact' computations in many academic fields. An extension of the methodology for use in the multilevel method is also described and developed.
- 講 師：
- Ajay Jasra (National University of Singapore)
- Introduction to Sequential Monte Carlo Methods and Multilevel Sequential Monte Carlo
- 日 時：
- 7月5日～7月19日 毎火曜日２限
- 場 所：