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]
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* '''Time: Thursday at 10am-12pm, Location: Bryan 509C'''
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* '''Time: Thursday at 4pm-4:50pm, Location: Jolley 431'''
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* '''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:
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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.
 
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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])
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* Wireless Health ([http://www.wirelesshealth2013.org/])
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* Wireless Health ([http://mobihealth.name/])
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* MobiCom ([http://www.sigmobile.org/mobicom/2013/])
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* MobiCom ([https://sigmobile.org/mobicom/2019/])
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* MobiSys ([http://www.sigmobile.org/mobisys/2013/])
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* MobiSys ([http://www.sigmobile.org/mobisys/2019/])
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* Sigcomm ([http://conferences.sigcomm.org/sigcomm/2013/])
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* Sigcomm ([http://conferences.sigcomm.org/sigcomm/2019/])
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* NSDI ([https://www.usenix.org/conference/nsdi14])
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* NSDI ([https://www.usenix.org/conference/nsdi19])
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* SOSP ([http://http://sigops.org/sosp/sosp13/])
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* SOSP ([https://www.sigops.org/])
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* OSDI ([https://www.usenix.org/conference/osdi14/])
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* OSDI ([https://www.usenix.org/conference/osdi18/])
  
  
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=== ---January 14, 2016 ---===
 
  
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'''Seminar -Chong'''
 
  
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Dynamoth: A Scalable Pub/Sub Middleware for Latency-Constrained Applications in the Cloud, McGill University, ICDCS’15, [http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7164934&tag=1 Paper]
 
  
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'''Lab Meeting -Dee'''
 
  
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=== ---January 21, 2016 ---===
 
  
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'''Seminar - Chao'''
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==Previous Semesters==
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Pandey, Navneet Kumar, et al. "Minimizing the Communication Cost of Aggregation in Publish/Subscribe Systems.", ICDCS’15, [http://msrg.org/publications/pdf_files/2015/agg15-Minimizing_the_Communication_Cost_of_Ag.pdf Paper]
 
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'''Lab Meeting -Yehan'''
 
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=== ---January 28, 2016 ---===
 
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'''Seminar - Haoran'''
 
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Cheng-Chun Tu, Michael Ferdman, et al ''A Comprehensive Implementation and Evaluation of Direct Interrupt Delivery'' VEE. 2015 [http://delivery.acm.org/10.1145/2740000/2731189/p1-tu.pdf?ip=128.252.20.193&id=2731189&acc=ACTIVE%20SERVICE&key=B63ACEF81C6334F5.4E6E072390D11401.4D4702B0C3E38B35.4D4702B0C3E38B35&CFID=749803384&CFTOKEN=43696593&__acm__=1454438150_2d4be17197fe5366ebe7aa5c513020a6 paper]
 
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'''Lab Meeting -Jing'''
 
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=== ---February 4, 2016 ---===
 
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'''Seminar -Dee'''
 
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Kinesis: A Security Incident Response and Prevention System for Wireless Sensor Networks slides, Sensys'14 [https://www.cerias.purdue.edu/assets/pdf/bibtex_archive/2013-12.pdf Paper]
 
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'''Lab Meeting -Chong'''
 
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=== ---February 11, 2016 ---===
 
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'''Seminar - Yehan'''
 
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Araujo, Jean, et al. "System architectures, protocols and algorithms for aperiodic wireless control systems." IEEE T IND INFORM. 2014. [Paper][http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=6514939&url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Farnumber%3D6514939]
 
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'''Lab Meeting -Chao'''
 
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=== ---February 18, 2016 ---===
 
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'''Seminar - Jing'''
 
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'''Lab Meeting -Haoran'''
 
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=== ---February 25, 2016 ---===
 
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'''Seminar -Chong'''
 
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'''Lab Meeting -Dee'''
 
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=== ---March 3, 2016 ---===
 
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'''Seminar - Chao'''
 
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'''Lab Meeting -Yehan'''
 
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=== ---March 10, 2016 ---===
 
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'''Seminar - Haoran'''
 
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'''Lab Meeting -Jing'''
 
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=== ---March 17, 2016 ---===
 
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'''Seminar -Dee'''
 
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'''Lab Meeting -Chong'''
 
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=== ---March 24, 2016 ---===
 
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'''Seminar - Yehan'''
 
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'''Lab Meeting -Chao'''
 
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=== ---March 31, 2016 ---===
 
  
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'''Seminar - Jing'''
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* [[Seminar Fall 2019|Fall 2019]]
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* [[Seminar Summer 2019|Summer 2019]]
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'''Lab Meeting -Haoran'''
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* [[Seminar Spring 2019|Spring 2019]]
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* [[Seminar Fall 2018|Fall 2018]]
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* [[Seminar Summer 2018|Summer 2018]]
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==Previous Semesters==
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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]]
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* [[Seminar Spring 2017|Spring 2017]]
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* [[Seminar Fall 2016|Fall 2016]]
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* [[Seminar Summer 2016|Summer 2016]]
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* [[Seminar Spring 2016|Spring 2016]]
 
* [[Seminar Fall 2015|Fall 2015]]
 
* [[Seminar Fall 2015|Fall 2015]]
 
* [[Seminar Summer 2015|Summer 2015]]
 
* [[Seminar Summer 2015|Summer 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

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