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UID:www.tcs.tifr.res.in/event/1064
DTSTAMP:20230914T125949Z
SUMMARY:Optimal Design of Queuing Systems via Compositional Stochastic Prog
 ramming
DESCRIPTION:Speaker: Ketan Rajawat (Department of Electrical Engineering\,\
 nIndian Institute of Technology\, Kanpur)\n\nAbstract: \nAbstract: Well-de
 signed queuing systems form the backbone of modern communications\, distri
 buted computing\, and content delivery architectures. Designs balancing in
 frastructure costs and user experience indices require tools from tele-tra
 ffic theory and operations research. A standard approach to designing such
  systems involves formulating optimization problems that strive to maximiz
 e the pertinent utility functions while adhering to quality-of-service and
  other physical constraints. In many cases\, formulating such problems nec
 essitates making simplistic assumptions on arrival and departure processes
  to keep the problem tractable.\n\nThis talks will introduce a stochastic 
 optimization framework for designing queuing systems where the exogenous p
 rocesses may have arbitrary and unknown distributions. We show that many s
 uch queuing design problems can generally be formulated as stochastic opti
 mization problems where the objective and constraints are non-linear funct
 ions of expectations. The compositional structure obviates the use of clas
 sical stochastic approximation approaches where the stochastic gradients a
 re often required to be unbiased. To this end\, a constrained stochastic c
 ompositional gradient descent algorithm is proposed that utilizes a tracki
 ng step for the expected value functions. The non-asymptotic performance o
 f the proposed algorithm is characterized by its iteration complexity. Fur
 ther improvements are proposed that build upon the primal-dual saddle poin
 t algorithm to result in zero constraint violation and O(T-0.25) optimalit
 y gap. Numerical tests allow us to validate the theoretical results and de
 monstrate the efficacy of the proposed algorithm.\n\nBio: Ketan Rajawat (S
 '06–M'12) received his B.Tech and M.Tech degrees in Electrical Engineeri
 ng from the Indian Institute of Technology (IIT) Kanpur\, India\, in 2007\
 , and his Ph.D. degree in Electrical and Computer Engineering from the Uni
 versity of Minnesota\, Minneapolis\, MN\, USA\, in 2012. He is currently a
 n Associate Professor in the Department of Electrical Engineering\, IIT Ka
 npur. His research interests are in the broad areas of signal processing\,
  robotics\, and communications networks\, with particular emphasis on dist
 ributed optimization and online learning. His current research focuses on 
 the development and analysis of distributed and asynchronous optimization 
 algorithms\, online convex optimization algorithms\, stochastic optimizati
 on algorithms\, and the application of these algorithms to problems in mac
 hine learning\, communications\, and smart grid systems. He is currently s
 erving as an Associate Editor with the IEEE Communications Letters and IEE
 E Transactions on Signal Processing. He is also the recipient of the 2018 
 INSA Medal for Young Scientists and the 2019 INAE Young Engineer Award.\n
URL:https://www.tcs.tifr.res.in/web/events/1064
DTSTART;TZID=Asia/Kolkata:20200616T140000
DTEND;TZID=Asia/Kolkata:20200616T150000
LOCATION:A-201 (STCS Seminar Room)
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