0


MCMC、SMC、,。。。下一步怎么办?

MCMC, SMC,... What next ?
课程网址: http://videolectures.net/acs07_moulines_mcm/  
主讲教师: Eric Moulines
开课单位: 巴黎ENST
开课时间: 2007-12-17
课程语种: 英语
中文简介:
蒙特卡罗方法最初是在计算机早期为统计物理学中的科学计算而开发的。由于计算机技术的快速进步以及对处理大型数据集和复杂系统的需求,在过去的二十年里,科学界对蒙特卡洛方法的兴趣激增。从计算生物学家到信号和图像处理工程师,再到金融计量经济学家,研究人员现在将蒙特卡洛技术视为推理的基本工具。除了使用流行的马尔可夫链蒙特卡罗策略及其自适应变体外,最近出现了各种序列蒙特卡罗策略,产生了大量新颖有效的推理和优化工具。在本次演讲中,我们将介绍我们认为的蒙特卡洛模拟中的“最新技术”,以进行推理,并试图确定下一个挑战。
课程简介: The Monte Carlo method was initially developed for scientific computing in statistical physics during the early days of the computers. Due to the rapid progress in computer technology and the need for handling large datasets and complex systems, the past two decades have witnessed a strong surge of interest in Monte Carlo methods from the scientific community. Researchers ranging from computational biologist to signal \& image processing engineers and to financial econometricians now view Monte Carlo techniques as essential tools for inference. Besides using the popular Markov chain Monte Carlo strategies and adaptive variants of it, various sequential Monte Carlo strategies have recently appeared on the scene, resulting in a wealth of novel and effective inferential and optimization tools. In this talk, we will present what we believe to be the "state-of-the art" in Monte-Carlo simulations for inference and will try to identify the next challenges.
关 键 词: 蒙特卡罗; 统计物理; 图像处理
课程来源: 视频讲座网
数据采集: 2023-06-11:chenxin01
最后编审: 2023-06-11:chenxin01
阅读次数: 12