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An online lecture on the topic of "What is Microgravity? Discovering Interesting Phenomena in Microgravity".This lecture of “Science World: Exploring Space to Benefit Mankind” Education Programme in the 2021/22 school year for secondary students, which aims to cultivate the interest of local youth in space science and elevate their enthusiasm for participating in the development of space technology.
- Subjects:
- Physics and Aeronautical and Aviation Engineering
- Keywords:
- Gravity Reduced gravity environments
- Resource Type:
- Video
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Video
What is your dream? And how to make it come true? Ms Guo Jingjing, the Olympic Gold Medalist, will share with us her story of chasing dreams.
你的夢想是什麼?你有好好努力使它實現嗎?奧運金牌得主郭晶晶女士將與大家分享她追逐夢想的故事。
Event Date: 22.11.2022
- Keywords:
- China Athletes -- Training of Diving
- Resource Type:
- Video
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Video
An online lecture on the topic of "Space Station’s Contribution to Space Resources and Human Developments".This lecture of “Science World: Exploring Space to Benefit Mankind” Education Programme in the 2021/22 school year for secondary students, which aims to cultivate the interest of local youth in space science and elevate their enthusiasm for participating in the development of space technology.
- Subjects:
- Industrial and Systems Engineering and Aeronautical and Aviation Engineering
- Keywords:
- Space stations Exploration of outer space
- Resource Type:
- Video
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Video
An online lecture on the topic of "Solar Vehicles for Space".This lecture of “Science World: Exploring Space to Benefit Mankind” Education Programme in the 2021/22 school year for secondary students, which aims to cultivate the interest of local youth in space science and elevate their enthusiasm for participating in the development of space technology.
- Subjects:
- Electrical Engineering
- Keywords:
- Solar energy Space vehicles -- Solar engines
- 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
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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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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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
【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】 During his tenure as PolyU President, Prof. Timothy W. Tong faced the challenge of changing the undergraduate curriculum from three years to four years. He led the restructure of the curriculum, enhancing it to focus more on the holistic development of students. In addition, Prof. Tong launched a number of initiatives to foster entrepreneurial abilities as well as cultural and artistic development among students. Watch the video now and learn more about the curriculum restructure in those days!
【理大八十五周年訪談系列】唐偉章教授在任理工大學校長期間,面對大學由三年制改為四年制的挑戰,帶領大學課程的革新,令理大教育更重視學生全人發展。此外,唐教授任內先後推出多項舉措,培育學生創業精神,以及文化和藝術的修養。立即看片,回顧當年改制點滴﹗
- Keywords:
- College presidents Hong Kong Polytechnic University Interviews Education Higher China -- Hong Kong Universities colleges
- Resource Type:
- Video
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