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機器學習與人工智能講壇:香港城市大學余雷博士報告通知

作者:統計機器智能與學習實驗室 來源:統計機器智能與學習實驗室 閱讀次數:198日期:2019/05/17

一、主題:Approximate Inference using Simplification of Gaussian Mixture Models
二、主講人:余雷博士 香港城市大學
三、時間:2019年05月20日上午10:00

四、地點:清水河校區主樓教工之家

五、主持人:計算機科學與工程學院 徐增林教授

六、內容簡介:

        Probabilistic modelling and Bayesian inference are principal tools which are widely used in machine learning. An assumption of simple probabilistic models can lead to tractable and efficient computation for inference, but usually it cannot fulfill the requirement of most cases of interest in real world applications. Monte Carlo sampling and variational approximation are the two mainstay approaches for approximate inference. MC sampling approximates the intractable probability distribution with samples, which can be accurate but time consuming. Variational approximation supposes an unknown variational distribution from a tractable family then determines it by solving an optimization problem, which is efficient but tedious mathe matical derivation is required for different models. Considering that finite mixture models are universal approximators for any continuous probability density, we use Gaussian Mixture Models(GMMs) to approximate generic continuous likelihoods in Bayesian inference. We firstly proposed a novel density simplification algorithm that can well preserve the original mixture distribution by directly grouping the base probability densities. Then we show its wide application on recursive Bayesian filtering, KDE mixture reduction, belief propagation and robust Gaussian Process regression.

七、主講人簡介:

        Lei Yu received the B.S. and M.S. degree in Information and Computing Science, and Computer Software and Theory from the Hunan Normal University, Changsha, China, in 2010 and 2013, respectively, and the Ph.D. degree in Computer Science from the City University of Hong Kong, in 2019. From 2011 to 2012, she was a visiting student in Department of Mathematics from Zhejiang University. From 2012 to 2013, she was an intern in Institute of Software Chinese Academy of Sciences (ISCAS). She is now working as a Research Associate in City University of Hong Kong.

八、主辦單位:計算機科學與工程學院(網絡空間安全學院)

  承辦單位:統計機器智能與學習實驗室(SMILE Lab)

 

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