Colloquium/Seminar

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Event(s) on September 2015


  • Monday, 14th September, 2015

    Title: Discriminative pattern mining and its applications in bioinformatics
    Speaker: Dr. HE Zengyou, School of Software, Dalian University of Technology, China
    Time/Place: 14:00  -  15:00
    FSC1217, Fong Shu Chuen Library, HSH Campus, Hong Kong Baptist University
    Abstract: Discriminative pattern mining is one of the most important techniques in data mining. This challenging task is concerned with finding a set of patterns that occur with disproportionate frequency in data sets with various class labels. Such patterns are of great value for group difference detection and classifier construction. Research on finding interesting discriminative patterns in class-labeled data evolves rapidly and lots of algorithms have been proposed to specifically address this problem. Discriminative pattern mining techniques have proven their considerable value in biological data analysis. The archetypical applications in bioinformatics include phosphorylation motif discovery, differentially expressed gene identification, discriminative genotype pattern detection, etc. In this talk, we first present an overview of discriminative pattern mining and the corresponding effective methods, and subsequently briefly illustrate their applications to tackling the bioinformatics problems. In particular, we present two algorithms for phosphorylation motif discovery that are designed based on the discriminative pattern mining techniques and one permutation-based method for assessing the statistical significance of phosphorylation motifs. In the end, we give a general discussion of potential challenges and future work for this task.


  • Monday, 21st September, 2015

    Title: Moreau's Proximity Operator: From Unilateral Mechanics to Data Science
    Speaker: Prof. Patrick L. Combettes, Laboratoire Jacques-Louis Lions, Université Pierre et Marie Curie - Paris 6 , France
    Time/Place: 17:00  -  18:00 (Preceded by Reception at 4:30pm)
    SCT909, Science Tower, HSH Campus, Hong Kong Baptist University
    Abstract: Proximity operators were introduced by Jean Jacques Moreau in 1962 in connection with problems in unilateral mechanics. They have recently become prominent tools in the modeling and the numerical solution of problems in data science. In this talk, an overview of proximity operators will be provided as well as recent developments in the area of complex structured optimization problems. Applications to machine learning, inverse problems, and image recovery will be discussed. Open conjectures and mathematical challenges in the field will also be presented.


  • Wednesday, 23rd September, 2015

    Title: Multilinear operators and Erdös-Falconer point configuration problems
    Speaker: Prof. Allan Greenleaf, Department of Mathematics, University of Rochester, USA
    Time/Place: 15:00  -  16:00
    FSC1217, Fong Shu Chuen Library, HSH Campus, Hong Kong Baptist University
    Abstract: Configuration problems of Erdös type concern counting the number of times that geometric configurations or quantities (lengths of line segments, areas of triangles, noncongruent simplices, etc.) occur among the points of a discrete set with a large number, N, of points. Falconer type problems are analogues of Erdös type problems in the setting of continuous geometry, where the cardinality N is replaced with a continuous measurement of size, namely a lower bound on the Hausdorff dimension. I will describe some of these problems and recent progress that has been made using estimates for multilinear operators.


  • Wednesday, 23rd September, 2015

    Title: The CMIV Short Course on Proximal Optimization
    Speaker: Prof. Patrick Louis COMBETTES, Pierre and Marie Curie University, France
    Time/Place: 16:00  -  18:00
    SCT909, Science Tower, HSH Campus, Hong Kong Baptist University


  • Friday, 25th September, 2015

    Title: HKBU MATH 45th Anniversary Distinguished Lecture -- Image Restoration: A Data-Driven Perspective
    Speaker: Prof. Zuowei Shen, Department of Mathematics, National University of Singapore, Singapore
    Time/Place: 16:30  -  17:30 (Preceded by Reception at 4:00pm)
    SCT909, Science Tower, HSH Campus, Hong Kong Baptist University
    Abstract: We are living in the era of big data. The discovery, interpretation and usage of the information, knowledge and resources hidden in all sorts of data to benefit human beings and to improve everyone's day to day life is a challenge to all of us. The huge amount of data we collect nowadays is so complicated, and yet what we expect from it is so much. It is hard to imagine that one can characterize these complicated data sets and solve real life problems by solving merely a few mathematical equations. However, generic mathematical models can be used to obtain a coarse level approximation (or low accuracy solution) to the answers we are seeking. The first question is how to use generic prior knowledge of the underlying solutions of the problem in hand and to set up a proper model for a good low level approximation? The second question is whether we are able to use the knowledge and information from the approximate solution derived from the given data to further improve the model itself so that more accurate solutions can be obtained? That is: how to engage an interactive data-driven approach to solve complex problems? As images are one of the most useful and commonly used types of data, in this talk, we review the development of the wavelet frame (or more general redundant system) based approach for image restoration from a data-driven perspective. We will observe that a good system for approximating any function, including images, should be capable of effectively capturing both global patterns and local features of the function. A wavelet frame is one of the examples of such a system. We will show how algorithms of the wavelet frame based image restoration are developed via the generic knowledge of images. Then, we will show how specific information of a given image can be used to further improve the models and algorithms. Through this process, we shall reveal some insights and understandings of the wavelet frame based approach for image restoration. We hope that this also leads to new ideas on how to analyse more complex data sets generated from other real life problems.


  • Wednesday, 30th September, 2015

    Title: The CMIV Short Course on Proximal Optimization
    Speaker: Prof. Patrick Louis COMBETTES, Pierre and Marie Curie University, France
    Time/Place: 16:00  -  18:00
    SCT909, Science Tower, HSH Campus, Hong Kong Baptist University