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Hong Kong Polytechnic University
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Year
2022
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Video
【PolyU 85th Anniversary Interview Series】 During his Chairmanship of the PolyU Council, Dr the Hon. Victor Lo Chung-wing invited the internationally renowned architect Dame Zaha Hadid to design the Jockey Club Innovation Tower, showcasing PolyU as a vibrant and innovative campus. In this interview, Dr Lo shares that he witnessed the development of another important building at PolyU. Do you know what it is?
【理大八十五周年訪談系列】羅仲榮博士出任理大校董會主席期間，邀請了國際知名的殿堂級建築師Dame Zaha Hadid 女士設計了賽馬會創新樓，為大學的建築群展現了創新形象。羅博士在訪談中更分享了任內見證理大另一重要設施的發展，你知道是甚麼嗎？
- Keywords:
- History Hong Kong Polytechnic University Interviews Education Higher College buildings Universities colleges China -- Hong Kong
- Resource Type:
- Video
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Video
【PolyU 85th Anniversary Interview Series】 Dr Sir Gordon Wu Ying-sheung assumed Chairmanship of the PolyU Council in 1997. Under his leadership of over six years, Sir Gordon guided a number of key PolyU campus development projects. He valued the positive impact hostel life brought to students and took part in the design of the PolyU’s first student hostel located in Hung Hom Bay. In this video, you will learn about Sir Wu’s views regarding education and whole person development as well as his wise words for young people.
【理大八十五周年訪談系列】 胡應湘爵士1997年出任理大校董會主席，在任六年領導理大校園多項重要發展，更親自參與理大第一所位於紅磡灣學生宿舍的設計，非常重視宿舍生活對大學生的成長。想知道胡爵士對學生全人教育的看法以及對年輕人的勸勉？立即看片。
- Keywords:
- History Hong Kong Polytechnic University Interviews Education Higher China -- Hong Kong Universities colleges College buildings
- Resource Type:
- Video
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Video
【PolyU 85th Anniversary Interview Series】 Prof. Poon Chung-kwong led PolyU for 18 years. During his tenure as President, PolyU assumed full university status and started a new chapter in its history. In this video, you will learn about how Prof. Poon positioned PolyU in unique roles, helping the University to excel in various aspects and laying a strong foundation for its long-term development.
【理大八十五周年訪談系列】 潘宗光教授帶領理大18年，出任校長期間，理大正式取得大學地位，開展了理大歷史新的一頁。潘教授任內爲理大發展確立獨特的定位，並取得驕人成績，爲理大長遠發展奠定堅實的基礎。立即看片。
- Keywords:
- College presidents History Hong Kong Polytechnic University Interviews Education Higher China -- Hong Kong Universities colleges
- Resource Type:
- Video
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Video
Before the advent of computers around 1950, optimization centered either on small-dimensional problems solved by looking at zeroes of first derivatives and signs of second derivatives, or on infinite-dimensional problems about curves and surfaces. In both cases, "variations" were employed to understand how a local solution might be characterized. Computers changed the picture by opening the possibility of solving large-scale problems involving inequalities, instead of only equations. Inequalities had to be recognized as important because the decisions to be optimized were constrained by the need to respect many upper or lower bounds on their feasibility. A new kind of mathematical analysis, beyond traditional calculus, had to be developed to address these needs. It built first on appealing to the convexity of sets and functions, but went on to amazingly broad and successful concepts of variational geometry, subgradients, subderivatives, and variational convergence beyond just that. This talk will explain these revolutionary developments and why there were essential.
Event date: 1/11/2022
Speaker: Prof. Terry Rockafellar (University of Washington)
Hosted by: Department of Applied Mathematics
- Subjects:
- Mathematics and Statistics
- Keywords:
- Convex functions Convex sets Mathematical optimization Computer science -- Mathematics
- Resource Type:
- Video
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Video
Geospatial information science is a discipline that focuses on using geospatial information technology to understand people, places, nature and processes of the earth. IoT refers to Internet of things, the combination of sensors, software and other technologies to connect and exchange data with other devices and systems over the Internet. The era of IoT brings us opportunities and challenges for geospatial information science. In the keynote, five characteristics and three scientific issues of geo-spatial information science in the era of IoT are summarised.
Even date: 6/9/2022
Speaker: Prof. Daren Li
Moderator: Prof. Christopher Chao (Hong Kong Polytechnic University)
Panel members: Prof. Qingyan Chen, Prof. Qinhao Chen (Hong Kong Polytechnic University)
Hosted by: PolyU Academy for Interdisciplinary Research
- Subjects:
- Land Surveying and Geo-Informatics
- Keywords:
- Internet of things Geospatial data Spatial data mining
- Resource Type:
- Video
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Video
Adaptive computation is of great importance in numerical simulations. The ideas for adaptive computations can be dated back to adaptive finite element methods in 1970s. In this talk, we shall first review some recent development for adaptive methods with some application. Then, we will propose a deep adaptive sampling method for solving PDEs where deep neural networks are utilized to approximate the solutions. In particular, we propose the failure informed PINNs (FI-PINNs), which can adaptively refine the training set with the goal of reducing the failure probability. Compared with the neural network approximation obtained with uniformly distributed collocation points, the proposed algorithms can significantly improve the accuracy, especially for low regularity and high-dimensional problems.
Event date: 18/10/2022
Speaker: Prof. Tao Tang (Beijing Normal University-Hong Kong Baptist University United International College)
Hosted by: Department of Applied Mathematics
- Subjects:
- Mathematics and Statistics
- Keywords:
- Sampling (Statistics) Differential equations Partial -- Numerical solutions Mathematical models Adaptive computing systems
- Resource Type:
- Video
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MOOC
The course describes the theoretical underpinnings of USR. It showcases some effective practices and activities carried out in institutions around the world. The course also promotes understanding of the USR concept, its implications, impacts, evaluation, possible implementation methods, and replicability. In doing so, it contributes to the expansion and consolidation of the USR movement. It provides a knowledge base for designing, planning, implementing, and evaluating programs from the fundamentals of USR and some existing good practices.
No prior knowledge is required to join the course. This course is for you especially if you are an administrator, a professor, or a professional staff member interested in learning new creative ways from the experts' at the universities to address the needs of society including SDGs (Sustainable Development Goals). If you are a government official or a foundation representative seeking ways to strengthen higher education, this course will help you explore future opportunities and directions.
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Video
Convex Matrix Optimization (MOP) arises in a wide variety of applications. The last three decades have seen dramatic advances in the theory and practice of matrix optimization because of its extremely powerful modeling capability. In particular, semidefinite programming (SP) and its generalizations have been widely used to model problems in applications such as combinatorial and polynomial optimization, covariance matrix estimation, matrix completion and sensor network localization. The first part of the talk will describe the primal-dual interior-point methods (IPMs) implemented in SDPT3 for solving medium scale SP, followed by inexact IPMs (with linear systems solved by iterative solvers) for large scale SDP and discussions on their inherent limitations. The second part will present algorithmic advances for solving large scale SDP based on the proximal-point or augmented Lagrangian framework In particular, we describe the design and implementation of an augmented Lagrangian based method (called SDPNAL+) for solving SDP problems with large number of linear constraints. The last part of the talk will focus on recent advances on using a combination of local search methods and convex lifting to solve low-rank factorization models of SP problems.
Event date: 11/10/2022
Speaker: Prof. Kim-Chuan Toh (National University of Singapore)
Hosted by: Department of Applied Mathematics
- Subjects:
- Mathematics and Statistics
- Keywords:
- Convex programming Semidefinite programming
- Resource Type:
- Video
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Video
We introduce a Dimension-Reduced Second-Order Method (DRSOM) for convex and nonconvex (unconstrained) optimization. Under a trust-region-like framework, our method preserves the convergence of the second-order method while using only Hessian-vector products in two directions. Moreover; the computational overhead remains comparable to the first-order such as the gradient descent method. We show that the method has a local super-linear convergence and a global convergence rate of 0(∈-3/2) to satisfy the first-order and second-order conditions under a commonly used approximated Hessian assumption. We further show that this assumption can be removed if we perform one step of the Krylov subspace method at the end of the algorithm, which makes DRSOM the first first-order-type algorithm to achieve this complexity bound. The applicability and performance of DRSOM are exhibited by various computational experiments in logistic regression, L2-Lp minimization, sensor network localization, neural network training, and policy optimization in reinforcement learning. For neural networks, our preliminary implementation seems to gain computational advantages in terms of training accuracy and iteration complexity over state-of-the-art first-order methods including SGD and ADAM. For policy optimization, our experiments show that DRSOM compares favorably with popular policy gradient methods in terms of the effectiveness and robustness.
Event date: 19/09/2022
Speaker: Prof. Yinyu Ye (Stanford University)
Hosted by: Department of Applied Mathematics
- Subjects:
- Mathematics and Statistics
- Keywords:
- Convex programming Nonconvex programming Mathematical optimization
- Resource Type:
- Video
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Others
A portfolio for ITC3089E showing how to present the theme and fabric
- Course related:
- ITC3089E Woven Fabric Design Project
- Subjects:
- Textiles
- Keywords:
- Weaving Textile fabrics
- Resource Type:
- Others