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DTSTART:20240310T070000
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DTSTART:20231105T060000
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UID:69cefae0c809d
DTSTART;TZID=America/Toronto:20240820T133000
SEQUENCE:0
TRANSP:TRANSPARENT
DTEND;TZID=America/Toronto:20240820T143000
URL:https://uwaterloo.ca/combinatorics-and-optimization/events/ura-seminar-
 ura-presentations-3
LOCATION:MC - Mathematics & Computer Building 200 University Avenue West Wa
 terloo ON N2L 3G1 Canada
SUMMARY:URA Seminar - URA Presentations
CLASS:PUBLIC
DESCRIPTION:SPEAKERS:\n  Mehrdad Sohrabi\, Zhisu Wang\, Jessica Ding\n\nSE
 MINAR TITLE: \n\nNotation of Total Dual Integrality for Semidefinite Progr
 amming\, \n\nFormal Method for Verifying the Security Cryptosystems\,\n\nM
 easures of Robustness and Efficiency of Convex Optimization\nAlgorithms\n\
 nLOCATION:\n M 5479\n\nThere will be a social starting at 1:00pm\n\nTITLE:
  Notation of Total Dual Integrality for Semidefinite Programming\n\nSPEAKE
 R: Mehrdad Sohrabi\n\nABSTRACT:\n\nTotal dual integrality (TDI) plays a cr
 ucial role in integer\nprogramming and polyhedral combinatorics\, with app
 lications in network\nflows\, matching\, and more. Semidefinite programmin
 g is an instance of\nconic optimization that generalizes linear programmin
 g. In this talk\,\nwe will discuss the notion of total dual integrality fo
 r semidefinite\nprogramming\, first introduced by M. K. Carli Silva and L.
  Tuncel. We\nwill also present the new results we obtained during this sem
 ester.\n\nTITLE: Formal Method for Verifying the Security Cryptosystems\n\
 nSPEAKER: Zhisu Wang\n\nABSTRACT:\n\nCryptoVerif is a security protocol ve
 rifier producing proofs presented\nas sequences of games\, like those manu
 ally written by cryptographers.\nWe introduce the basic syntax of CryptoVe
 rif with an example of\nproving a simple primitive. Then we show the attem
 pts to apply this\ntool on more complex cryptographic protocols.\n\nTITLE:
  Measures of Robustness and Efficiency of Convex Optimization\nAlgorithms\
 n\nSPEAKER: Jessica Ding\n\nABSTRACT:\n\nInterior point method solvers hav
 e proven to be an effective tool for\nsolving linear and non-linear convex
  optimization problems. In this\ntalk I will introduce some measures of ro
 bustness and efficiency of\nconvex optimization algorithms as well as intu
 ition behind them. We\nwill learn about the property of ill-poisedness and
  how it influences\nthe efficiency and correctness of solvers. I will also
  show some of\nthe results from the experiments we ran over the term.
DTSTAMP:20260402T232520Z
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