0


采用机器学习方法的系统辨识

System Identification Using Machine Learning Methods
课程网址: http://videolectures.net/bbci2012_wichmann_system_identification/  
主讲教师: Wichmann Felix A
开课单位: 马克斯普朗克研究所
开课时间: 2012-12-03
课程语种: 英语
中文简介:
在行为层面上理解感知和潜在的认知过程需要解决特征识别问题:哪些特征是感官系统基于其计算得出的?我们可以使用什么技术来识别它们?因此,心理物理学中的一个核心挑战是系统识别:我们需要推断出人类观察者在看到或听到时使用的关键特征或线索。如果面对现实世界中复杂的刺激,视觉或听觉刺激的哪个方面实际上会影响行为?在我的实验室中,我们开发了基于现代机器学习方法的探索性数据驱动系统识别技术,从人类行为判断中推断出关键特征。我将介绍这些方法,并说明它们相对于传统的“反向相关”方法和“气泡技术”的好处。
课程简介: Understanding perception and the underlying cognitive processes on a behavioral level requires a solution to the feature identification problem: Which are the features on which sensory systems base their computations? What techniques can we use to identify them? Thus one of the central challenges in psychophysics is System Identification: We need to infer the critical features, or cues, human observers make use of when they see or hear. What aspect of the visual or auditory stimulus actually influences behaviour if faced with real-world, complex stimuli? In my laboratory we have developed exploratory, data-driven system identification techniques based on modern machine learning methods to infer the critical features from human behavioural judgments. I will present these methods and show what their benefits are over the traditional “reverse-correlation” approach and the “bubbles technique”.
关 键 词: 特征识别问题; 系统辨识; 数据驱动; 机器学习方法
课程来源: 视频讲座网
最后编审: 2020-07-29:yumf
阅读次数: 131