31
2023-03
10:00 - 11:00
Influence of defects on polarization in ferroelectrics: a phase-field study by Dr.Xiaoxing Cheng
Speaker: Dr.Xiaoxing Cheng Topic: Influence of defects on polarization in ferroelectrics: a phase-field study by Dr.Xiaoxing Cheng Time & Date: on March 31 (Friday) 10:00-11:00 (Beijing Time) Zoom Meeting: https://cuhk-edu-cn.zoom.us/j/96295554527?pwd=cUpyZmkxaWZKOVc2M29QS1B2V3BOQT09 Zoom Meeting ID: 962 9555 4527 Password​:123456 Abstract: Ferroelectric is a large group of functional materials that possesses outstanding ferroelectric, piezoelectric, dielectric properties, and a wide range of applications, such as capacitors, actuators, transducers, random access memories, waveguid…
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28
2023-03
10:30 - 12:15
“AI安全与隐私”系列论坛第19期:实战ChatGPT
论坛议程 #1 开场主持 嘉宾: 吴保元教授 香港中文大学(深圳)数据科学学院副教授,深圳大数据研究院大数据安全计算实验室主任 时间:10:30-10:35   #2 主题报告 嘉宾: 胡侠教授 莱斯大学计算机科学系副教授,数据科学中心主任,AIPOW联合创始人 报告题目: ChatGPT in Action: An Experimental lnvestigation of lts Effectiveness in NLP Tasks 实战ChatGPT: ChatGPT在自然语言处理中的实验性探索 时间:10:35-11:25   #3 问答环节 时间:11:25-11:35   #4 圆桌研讨 嘉宾: 胡侠教授 徐迈教授 赫然教授 吴保元教授 研讨主题: ① The impact of the emergence of ChatGPT on the development of human society and AI      ChatGPT的出现对人类社会和AI发展的影响 ②  New security challenges and ethical issues posed by chatGPT      ChatGPT带…
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16
2023-03
09:00 - 10:00
An effective metaheuristic for the last mile delivery with roaming delivery locations and stochastic travel times by Dr.Yandong He
Speaker: Dr.Yandong He Topic: An effective metaheuristic for the last mile delivery with roaming delivery locations and stochastic travel times by Dr.Yandong He Time & Date: on March 16 (Thursday) 09:00-10:00 (Beijing Time) Zoom Meeting: https://cuhk-edu-cn.zoom.us/j/91425379503?pwd=ZGNGR1o2WTJ0Wm5LNTNkS014NVN4QT09 Zoom Meeting ID: 914 2537 9503 Password​:123456 Abstract: We consider the last mile delivery system with roaming delivery locations and stochastic travel times. The problem is formulated as a two-stage stochastic programming model with recourses, its objective is to mini…
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28
2023-02
10:00 - 11:00
Machine Learning-Assisted Design of Electrode Microstructures and Flow Fields for Redox Flow Batteries by Dr.Shuaibin Wan
Speaker: Dr.Shuaibin Wan Topic: Machine Learning-Assisted Design of Electrode Microstructures and Flow Fields for Redox Flow Batteries Time & Date: 10:00 -11:00,Tuesday,February 28, 2023 (Beijing time) Zoom Meeting: https://cuhk-edu-cn.zoom.us/j/95604643160?pwd=eWJmNkpUN3ovZlRhdHVEN1ByV2FSZz09 Zoom Meeting ID:956 0464 3160 Password:123456 Abstract: Redox flow batteries (RFBs) offer a reliable solution for long-term and grid-scale storage of renewable energy. However, the lack of effective approaches to designing electrodes and flow fields limits the performance of RFBs. In this tal…
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06
2023-03
10:00 - 11:00

DY103 & Zoom

“Mathematical Programming Computation” Seminar Series: Dr. Xijun Li
“Mathematical Programming Computation” Seminar Series: Dr. Xijun Li Organizers: Shenzhen Research Institute of Big Data (深圳市大数据研究院 in Chinese)                Shenzhen International Center for Industrial and Applied Mathematics (深圳国际工业与应用数学中心 in Chinese) Speaker: Dr. Xijun Li Language: English Talk title: Order matters: Boosting Mathematical Solver via Machine Learning Techniques Talk abstract: The trend of using machine learning techniques to improve the mathematical programming solvers has recently drawn lots of attention. In this talk, we will first restate an easily overlooked problem…
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13
2023-03
16:00 - 17:00

Zoom

“Mathematical Programming Computation” Seminar Series: Dr. Timo Berthold
Organizers: Shenzhen Research Institute of Big Data (深圳市大数据研究院 in Chinese)                    Shenzhen International Center for Industrial and Applied Mathematics (深圳国际工业与应用数学中心 in Chinese) Speaker: Dr. Timo Berthold Language: English Talk title: Machine Learning inside MIP solvers Talk abstract: Modern MIP solvers consist of many subroutines that take care of different aspects of the solution process: presolving, cut generation, cut selection, primal heuristics, and so forth. For a given MIP, the solver has to make online decisions on which of multiple alternative instantiations of a sub…
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16
2023-01
14:00 - 15:00

Zoom

Deep Reinforcement learning and its commercial applications
Speaker: Dr. Liang Zhang Topic:  Deep Reinforcement learning and its commercial applications Time & Date: 14:00 -15:00, Tuesday,January 16, 2023 (Beijing time) Zoom Meeting: https://cuhk-edu-cn.zoom.us/j/98058735363?pwd=RDZRRnVkd09oSmhVL1lKd212ODkzZz09 Zoom Meeting ID:980 5873 5363 Password:123456 Abstract: Since Google's AlphaGo outperformed the level of human in Go, reinforcement learning has proven its excellent ability in multiple game scenarios. At present, many research works continue to improve the ability of reinforcement learning algorithms to make them more efficient, fas…
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17
2023-01
10:30 - 11:30

Zoom

SRIBD Seminar:Deep speaker embedding learning and applications to related tasks by Dr. Shuai Wang(Online)
Speaker: Dr. Shuai Wang Topic:  Deep speaker embedding learning and applications to related tasks Time & Date: 10:30 -11:30, Tuesday,January 17, 2023 (Beijing time) Zoom Meeting: https://cuhk-edu-cn.zoom.us/j/94045186370?pwd=TWI5WmRRU2Z2aGh5U0dlMXBOMTJkUT09 Zoom Meeting ID:940 4518 6370 Password:123456 Abstract: Speaker embeddings are low-dimensional representations of a speaker's voice that capture his unique characteristics. They are commonly used for tasks where speaker identity should be modeled. In this talk, I will introduce several approaches for improving speaker embedding'…
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13
2023-01
10:00 - 11:00

DY103&Zoom

SRIBD Seminar:Network Revenue Management Under a Spiked Multinomial Logit Choice Model
Speaker: Dr.Yufeng Cao   Topic: SRIBD Seminar:Network Revenue Management Under a Spiked Multinomial Logit Choice Model Abstract: Airline booking data have shown that the fraction of customers who choose the cheapest available fare class often is much greater than that predicted by the multinomial logit choice model calibrated with the data. For example, the fraction of customers who choose the cheapest available fare class is much greater than the fraction of customers who choose the next cheapest available one, even if the price difference is small. To model this spike in demand for the chea…
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