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Seminar on Internet Technologies (Winter 2022/2023): Difference between revisions

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Seminar on Internet Technologies (Winter 2022/2023) (view source)

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(Created page with "== Details == {{CourseDetails |credits=5 ECTS (BSc/MSc AI); 5 (ITIS) |lecturer=[http://user.informatik.uni-goettingen.de/~fu Prof. Xiaoming Fu] |ta =[http://www.net.informat...")
 
 
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|ta = Tingting Yuan [tingting.yuan@cs.uni-goettingen.de]
|ta = Tingting Yuan [tingting.yuan@cs.uni-goettingen.de]
|time='''Please read this introduction slide [https://docs.google.com/presentation/d/13hmKYBmB4tbTFNeK1GvBAs1qZntMYo75o8ycb1NgYXI/edit?usp=sharing]. If there is any question, please contact teaching assistants.'''
|time='''Please read this introduction slide [https://docs.google.com/presentation/d/13hmKYBmB4tbTFNeK1GvBAs1qZntMYo75o8ycb1NgYXI/edit?usp=sharing]. If there is any question, please contact teaching assistants.'''
|univz=[https://univz.uni-goettingen.de/qisserver/rds?state=verpublish&status=init&vmfile=no&publishid=302541&moduleCall=webInfo&publishConfFile=webInfo&publishSubDir=veranstaltung]}}
}}


==Announcement==
==Announcement==
No open talk. You can contact your topic advisor to schedule a 1V1 meeting or talk.
No open talk. You can contact your topic advisor to schedule a 1V1 meeting or talk.
'''!! 25.06 deadline for registration on Flexnow'''


==Course description==
==Course description==
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==Schedule==
==Schedule==
* '''24.06.2022 ''': Deadline for registration to attend the final presentation
* '''23.01.2023''': Deadline for registration to attend the final presentation
* '''19.07.2022 2PM-3PM''' : Final Presentations (IFI 1.101)
* '''02.02.2023''' : Final Presentations (IFI 0.101)
* '''12.08.2022 (23:59) ''': Deadline for submission of the report (should be sent to the topic adviser!).
* '''24.02.2023 (23:59) ''': Deadline for submission of the report (should be sent to the topic adviser!).


== Topics ==
== Topics ==
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|{{Hl2}} |'''Available'''
|{{Hl2}} |'''Available'''
|-
|-
| Video analytics with deep reinforcement learning
| Network management with deep reinforcement learning
| In this topic, you will study deep reinforcement learning used in video analytics.
| In this topic, you will study deep reinforcement learning used in network management, e.g., traffic congestion control, and adaptive bitrate streaming.
| Basic programming knowledge, Basic machine learning knowledge, need coding work
| Basic programming knowledge, Basic machine learning knowledge, need coding work
| [Tingting Yuan, tingting.yuan@cs.uni-goettingen.de]
| [Tingting Yuan, tingting.yuan@cs.uni-goettingen.de]
|
|
| Yes
| No
|-
|-
|-
|-
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|[https://topten.ai/ai-painting-generators/]
|[https://topten.ai/ai-painting-generators/]
| Yes
| Yes
|-
|-
|Running neural-network-based applications on mobile devices
| In this topic, you will study how to partition application processing pipelines, e.g., scaling face recognition.
| Basic programming knowledge, Basic machine learning knowledge
| [Weijun Wang, weijun.wang@informatik.uni-goettingen.de]
|[https://dl.acm.org/doi/pdf/10.1145/3372224.3380881]
| Yes
|-
|-
|Running neural network on Multiple CPUs/GPUs or heterogeneous hardware
| In this topic, you will study how to fine-grained partition NN and schedule them on multiple hardware.
| Basic programming knowledge, Basic machine learning knowledge
| [Weijun Wang, weijun.wang@informatik.uni-goettingen.de]
|[https://dl.acm.org/doi/pdf/10.1145/3341301.3359658][https://dl.acm.org/doi/pdf/10.1145/3458864.3467882]
| Yes
|-
|-
|Physics-informed neural networks: Principles, Case studies, and Prospects
| In this project, you will be devoted to solving a specific problem using physics-informed neural networks with a small set of existing experimental data. The student is expected to be interested in the interdisciplinary subject of physics and computer science.
| Basic programming knowledge, Basic machine learning knowledge
| [Yunxiao Zhang, yunxiao.zhang@ds.mpg.de]
|[https://www.nature.com/articles/s42254-021-00314-5]
| Yes
|-
|-
|-
| Change Detection in Satellite Image Time Series
| Change Detection in Satellite Image Time Series
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|-
|-
| Social Media Comments Network
| Social Media Comments Network
| In this topic, you will study methods to crawl the dataset from social networks and utilizing social science network analysis in any topic you are interested in (science/education/politics…) to find out the network structure and compare the difference among different topics.
| In this topic, you will study methods to crawl the dataset from social networks and utilize social science network analysis in any topic you are interested in (science/education/politics…) to find out the network structure and compare the difference among different topics.
| Basic programming knowledge
| Basic programming knowledge
| [Zhengze Li, zhengze.li@cs.uni-goettingen.de]
| [Zhengze Li, zhengze.li@cs.uni-goettingen.de]
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|
|
| No
| No
|-
|-
| Open topics
| Topics regarding to computer science
|
| [Zhengze Li, zhengze.li@cs.uni-goettingen.de]
|
| Yes
|-
|-
|-
|-
Yuan4
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