Colloquium/Seminar

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Coming event(s)


  • Monday, 30th July, 2018

    Title: An assembly and decomposition (AD) approach for constructing separable minorizing functions in a class of MM algorithms
    Speaker: Prof Guo-Liang TIAN, Department of Mathematics, Southern University of Science and Technology, Shenzhen, China
    Time/Place: 14:00  -  15:00
    FSC1111, Fong Shu Chuen Library, HSH Campus, Hong Kong Baptist University
    Abstract: The minorization-maximization (MM) principle provides an important and useful tool for optimization problems and has a broad range of applications in statistics because of its conceptual simplicity, ease of implementation and numerical stability. A key step in developing an MM algorithm is to construct an appropriate minorizing function. This is quite challenging to many practitioners as it has to be done case by case and its success often involves and heavily depends on a clever and specific use of Jensen's inequality or a similar kind. To address this problem, in this paper, we propose a new assembly and decomposition (AD) approach which successfully constructs separable minorizing functions in a general class of MM algorithms. The AD approach constructs a minorizing function by employing two novel techniques which we refer to as the assembly technique (or A-technique) and the decomposition technique (or D-technique), respectively. The A-technique first introduces the notions of assemblies and complemental assembly, consisting of several families of concave functions that have arisen in numerous applications. The D-technique then cleverly decomposes the high-dimensional objective function into a sum of one-dimensional functions to construct minorizing functions as guided and facilitated by the A-technique. We demonstrate the utility of the proposed approach in diverse applications which result in novel algorithms with theoretical and numerical advantages. Extensive numerical studies are provided to assess its finite-sample performance. Further extensions of the AD techniques are also discussed. (This is a joint work with Miss Xifen HUANG and Dr. Jinfeng XU)


  • Friday, 3rd August, 2018

    Title: Blockchain Design for Supply Chain Management
    Speaker: Prof SHI Junmin, Martin Tuchman School of Management, New Jersey Institute of Technology, Newark, USA
    Time/Place: 11:00  -  12:00
    FSC1217, Fong Shu Chuen Library, HSH Campus, Hong Kong Baptist University
    Abstract: Blockchain research is still in its infancy stage, with most exiting work focused on security and scalability and few applications for controlling physical devices. Very scant research looks at its impact and design issues on management perspectives, especially from the perspective of Supply Chain Management. To investigate the impact of blockchain technology (BCT) on supply chain performance and the inherent design issue, we study a generic stochastic model, where a manufacturer seeks to maximize the total expected discounted profit, by jointly managing (i) blockchain design, (ii) production or ordering decision, and (iii) dynamic pricing and selling. The leverage of blockchain can help firms reduce order quantity, lower selling price and reduce the target inventory level to carry over. It is also shown that the volatility pertaining to either supply or demand market will lower the expected profit. While facing higher volatility, the firm prefers to leverage high degree of blockchain. Finally, our numerical study illustrates rich managerial insight. For example, considering tech-savvy customer behavior, some types of goods (e.g., credence goods and experience goods) appreciate BCT, but it might not be beneficial to leverage BCT for some others (e.g., Search goods); considering the lifecycle of the product, it is recommended to adopt BCT as early as possible and leverage a higher adoption degree at an earlier stage; high volatility of supply chain (e.g., yield and demand) raises the intension to adopt BCT.