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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=== ---May 19  2016 ---===
 
  
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'''Seminar - Chao'''
 
  
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Grosvenor, Matthew P., et al. "Queues don’t matter when you can JUMP them!.", NSDI'15. [https://www.usenix.org/system/files/conference/nsdi15/nsdi15-paper-grosvenor_update.pdf PDF]
 
  
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'''Lab Meeting - Yehan'''
 
  
  
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=== ---May 26  2016 ---===
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==Previous Semesters==
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'''Seminar - Dee'''
 
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Node or Link? Fine-Grained Analysis of Packet-Loss Attacks in Wireless Sensor Networks, ACM Transactions on Sensor Networks (TOSN), May 2016.
 
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'''Lab Meeting - Jing'''
 
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=== ---June 2  2016 ---===
 
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'''Seminar - Chong'''
 
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'''Lab Meeting - Haoran'''
 
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=== ---June 23  2016 ---===
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* [[Seminar Fall 2019|Fall 2019]]
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* [[Seminar Summer 2019|Summer 2019]]
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'''Seminar - Yehan'''
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* [[Seminar Spring 2019|Spring 2019]]
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* [[Seminar Fall 2018|Fall 2018]]
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Teixeira, André, et al. "A secure control framework for resource-limited adversaries." Automatica 51 (2015)
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* [[Seminar Summer 2018|Summer 2018]]
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* [[Seminar Spring 2018|Spring 2018]]
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'''Lab Meeting - Chao'''
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* [[Seminar Fall 2017|Fall 2017]]
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* [[Seminar Summer 2017|Summer 2017]]
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=== ---June 30  2016 ---===
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* [[Seminar Spring 2017|Spring 2017]]
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* [[Seminar Fall 2016|Fall 2016]]
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'''Seminar - Jing'''
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* [[Seminar Summer 2016|Summer 2016]]
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Yang, Maolin, Alexander Wieder, and Björn B. Brandenburg. "Global real-time semaphore protocols: A survey, unified analysis, and comparison." Real-Time Systems Symposium, 2015.
 
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'''Lab Meeting - Chong'''
 
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=== ---July 7  2016 ---===
 
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'''Seminar - Haoran'''
 
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A Real-Time Scratchpad-centric OS for Multi-core Embedded Systems (RTAS'16) [http://2016.rtas.org/wp-content/uploads/2016/06/68.pdf Presentation]
 
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Rohan Tabish, Renato Mancuso, Saud Wasly, Ahmed Alhammad, Sujit S. Phatak, Rodolfo Pellizzoni and Marco Caccamo [http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7461321 paper]
 
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'''Lab Meeting - Dee'''
 
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=== ---July 14  2016 ---===
 
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'''Seminar - Chao'''
 
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Q. Perret, P. Maurere, E. Noulard, C. Pagetti, P. Sainrat and B. Triquet, "Temporal Isolation of Hard Real-Time Applications on Many-Core Processors," 2016 IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS), Vienna, 2016, pp. 1-11. [http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7461363&tag=1 pdf]
 
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'''Lab Meeting - Yehan'''
 
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=== ---July 21  2016 ---===
 
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'''Seminar - Dee'''
 
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Oppcast: Exploiting Spatial and Channel Diversity for Robust Data Collection in Urban Environments, IPSN'16 [http://www.comp.nus.edu.sg/~mobashir/Resources/Papers/2016ipsn.pdf Paper]
 
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'''Lab Meeting - Jing'''
 
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=== ---July 28  2016 ---===
 
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'''Seminar - Yehan'''
 
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'''Lab Meeting - Haoran'''
 
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=== ---August 4  2016 ---===
 
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'''Seminar - Jing'''
 
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'''Lab Meeting - Chao'''
 
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=== ---August 11  2016 ---===
 
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=== ---August 18  2016 ---===
 
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==Previous Semesters==
 
 
* [[Seminar Spring 2016|Spring 2016]]
 
* [[Seminar Spring 2016|Spring 2016]]
 
* [[Seminar Fall 2015|Fall 2015]]
 
* [[Seminar Fall 2015|Fall 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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