Difference between revisions of "CSE730x Research Seminar"

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* '''Instructor:''' [http://www.cse.wustl.edu/~lu Prof. Chenyang Lu]
 
* '''Instructor:''' [http://www.cse.wustl.edu/~lu Prof. Chenyang Lu]
* '''Time: Thursday at 10am-12pm, Location: Bryan 509C'''
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* '''Time: Thursday at 4pm-4:50pm, Location: Jolley 431'''
* '''Google group:''' [http://groups.google.com/group/wu-systems-seminar google group]
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* '''Google group:''' [https://groups.google.com/forum/#!forum/wustlmlseminar group for machine learning seminar]
  
 
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This seminar examines machine learning by studying seminal papers and recent research results. Each semester, the seminar emphasizes different themes reflecting the current research interests of the participants. The theme of this semester's seminar is '''Machine Learning for Health'''. We will read and discuss papers from recent major conferences on machine learning, data mining, and AI related to healthcare.  These conferences include:
This seminar examines fundamental and emerging concepts in concurrency and distribution by studying seminal papers and recent research results.  Broad topics of interest include models of concurrency, mobile computing, parallel architectures, sensor networks, distributed algorithms, and specialized protocols. Each semester, the seminar emphasizes different themes reflecting the current research interests of the participants.
 
 
 
The theme of this semester's seminar is Wireless Sensor Networks. We will read and discuss papers from recent major conferences on mobile, wireless, and sensor networks and systems.  These conferences include:
 
  
 
* SenSys ([http://sensys.acm.org])
 
* SenSys ([http://sensys.acm.org])
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* RTAS ([http://www.rtas.org/])
 
* RTAS ([http://www.rtas.org/])
 
* ICCPS ([http://www.iccps.org])
 
* ICCPS ([http://www.iccps.org])
* Wireless Health ([http://www.wirelesshealth2013.org/])
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* Wireless Health ([http://mobihealth.name/])
* MobiCom ([http://www.sigmobile.org/mobicom/2013/])
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* MobiCom ([https://sigmobile.org/mobicom/2019/])
* MobiSys ([http://www.sigmobile.org/mobisys/2013/])
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* MobiSys ([http://www.sigmobile.org/mobisys/2019/])
* Sigcomm ([http://conferences.sigcomm.org/sigcomm/2013/])
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* Sigcomm ([http://conferences.sigcomm.org/sigcomm/2019/])
* NSDI ([https://www.usenix.org/conference/nsdi14])
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* NSDI ([https://www.usenix.org/conference/nsdi19])
* SOSP ([http://http://sigops.org/sosp/sosp13/])
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* SOSP ([https://www.sigops.org/])
* OSDI ([https://www.usenix.org/conference/osdi14/])
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* OSDI ([https://www.usenix.org/conference/osdi18/])
  
  
=== ---August 20, 2015 ---===
 
  
'''Seminar - Yunkun'''
 
  
Zaharia, Matei, et al. [https://www.usenix.org/system/files/conference/nsdi12/nsdi12-final138.pdf "Resilient distributed datasets: A fault-tolerant abstraction for in-memory cluster computing."] Proceedings of the 9th USENIX conference on Networked Systems Design and Implementation. USENIX Association, 2012.
 
  
'''Lab Meeting -Bo'''
 
  
=== ---August 27, 2015 ---===
 
  
'''Seminar - Chao'''
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==Previous Semesters==
 
 
Kolchinsky, Ilya, Izchak Sharfman, and Assaf Schuster. [http://dl.acm.org/citation.cfm?id=2771832 "Lazy evaluation methods for detecting complex events."] Proceedings of the 9th ACM International Conference on Distributed Event-Based Systems. ACM, 2015.
 
 
 
'''Lab Meeting -Chong'''
 
 
 
=== ---September 3, 2015 ---===
 
 
 
'''Seminar - Dee'''
 
 
 
'''Lab Meeting -Jing'''
 
 
 
 
 
=== ---September 10, 2015 ---===
 
 
 
'''Seminar - Chong'''
 
 
 
Wormhole: Reliable Pub-Sub to support Geo-replicated Internet Services, Sharma, Yogeshwer et al. NSDI'15 [https://www.usenix.org/system/files/conference/nsdi15/nsdi15-paper-sharma.pdf Paper]
 
 
 
'''Lab Meeting -Yunkun'''
 
 
 
=== ---September 17, 2015 ---===
 
 
 
'''Seminar - Jing'''
 
 
 
Ousterhout, Kay, et al. [http://www.eecs.berkeley.edu/~keo/publications/sosp13-final17.pdf "Sparrow: distributed, low latency scheduling."] Proceedings of the Twenty-Fourth ACM Symposium on Operating Systems Principles. ACM, 2013. (SOSP 13)
 
 
 
'''Lab Meeting -Chao'''
 
 
 
=== ---September 24, 2015 ---===
 
 
 
'''Seminar - Yehan'''
 
 
 
'''Lab Meeting -Dee'''
 
 
 
 
 
=== ---October 1, 2015 ---===
 
 
 
'''Seminar - Haoran'''
 
 
 
'''Lab Meeting -Bo'''
 
 
 
 
 
=== ---October 8, 2015 ---===
 
 
 
'''Seminar - Yunkun'''
 
 
 
'''Lab Meeting -Jing'''
 
  
 
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* [[Seminar Fall 2019|Fall 2019]]
=== ---October 15, 2015 ---===
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* [[Seminar Summer 2019|Summer 2019]]
 
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* [[Seminar Spring 2019|Spring 2019]]
'''Seminar - Dee'''
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* [[Seminar Fall 2018|Fall 2018]]
 
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* [[Seminar Summer 2018|Summer 2018]]
'''Lab Meeting -Yehan'''
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* [[Seminar Spring 2018|Spring 2018]]
 
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* [[Seminar Fall 2017|Fall 2017]]
 
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* [[Seminar Summer 2017|Summer 2017]]
=== ---October 22, 2015 ---===
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* [[Seminar Spring 2017|Spring 2017]]
 
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* [[Seminar Fall 2016|Fall 2016]]
'''Seminar - Chao'''
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* [[Seminar Summer 2016|Summer 2016]]
 
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* [[Seminar Spring 2016|Spring 2016]]
'''Lab Meeting -Chong'''
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* [[Seminar Fall 2015|Fall 2015]]
 
 
 
 
=== ---October 29, 2015 ---===
 
 
 
'''Seminar - Haoran'''
 
 
 
'''Lab Meeting -Yunkun'''
 
 
 
 
 
=== ---November 5, 2015 ---===
 
 
 
'''Seminar - Jing'''
 
 
 
'''Lab Meeting -Chao'''
 
 
 
 
 
=== ---November 12, 2015 ---===
 
 
 
'''Seminar - Chong'''
 
 
 
'''Lab Meeting -Dee'''
 
 
 
 
 
==Previous Semesters==
 
 
* [[Seminar Summer 2015|Summer 2015]]
 
* [[Seminar Summer 2015|Summer 2015]]
 
* [[Seminar Spring 2015|Spring 2015]]
 
* [[Seminar Spring 2015|Spring 2015]]
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==Previous Lab Meetings==
 
==Previous Lab Meetings==
 +
* [[Labmeeting Spring 2020|Spring 2020]]
 
* [[Labmeeting Fall 2014|Fall 2014]]
 
* [[Labmeeting Fall 2014|Fall 2014]]
 
* [[Labmeeting Summer 2014|Summer 2014]]
 
* [[Labmeeting Summer 2014|Summer 2014]]
 
* [[Labmeeting Spring 2014|Spring 2014]]
 
* [[Labmeeting Spring 2014|Spring 2014]]

Latest revision as of 21:49, 9 January 2020

This seminar examines machine learning by studying seminal papers and recent research results. Each semester, the seminar emphasizes different themes reflecting the current research interests of the participants. The theme of this semester's seminar is Machine Learning for Health. We will read and discuss papers from recent major conferences on machine learning, data mining, and AI related to healthcare. These conferences include:




Previous Semesters

Previous Lab Meetings