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BEGIN:VEVENT
UID:6a9c050ccf053
DTSTART;TZID=America/Toronto:20260807T100000
SEQUENCE:0
TRANSP:TRANSPARENT
DTEND;TZID=America/Toronto:20260807T110000
URL:https://uwaterloo.ca/combinatorics-and-optimization/events/masters-thes
 is-presentation-ziwen-wang-solving-linear
SUMMARY:Master's Thesis Presentation - ZiWen Wang - Solving Linear Programs
 \nwith very Tall Constraint Matrices
CLASS:PUBLIC
DESCRIPTION:SPEAKER: \n ZiWen Wang\n\nSUPERVISOR:\n Levent Tuncel\n\nLOCAT
 ION:\n MC 5479\n\nABSTRACT: \n\nGiven an LP with tall and skinny constrai
 nt matrix\, we will\nexploit this property and study an algorithm invent
 ed by Clarkson\n[8]. Although this algorithm has\nbeen around for over 30
  years\, there were no software or\nimplementation that could be found on
 line\, nor there be any\nbenchmarks for these special tall and skinny LP 
 s. We will describe\nsome variants and changes to the algorithm aiming f
 or practical\nperformancesto close this gap.\n\nWe also study a first orde
 r algorithm aimed for large scale LP\ns proposed by a group of researche
 rs from Google [2]\, [3] called\nPDLP. And compare it with Clarkson’s a
 lgorithm.
DTSTAMP:20260905T120324Z
END:VEVENT
BEGIN:VEVENT
UID:6a9c050cd08b0
DTSTART;TZID=America/Toronto:20260807T110000
SEQUENCE:0
TRANSP:TRANSPARENT
DTEND;TZID=America/Toronto:20260807T120000
URL:https://uwaterloo.ca/combinatorics-and-optimization/events/masters-thes
 is-presentation-amaan-khan-study-first-order
SUMMARY:Master's Thesis Presentation - Amaan Khan - A Study of First-Order\
 nPrimal-Dual Algorithms for Linear Optimization
CLASS:PUBLIC
DESCRIPTION:SPEAKER: \n Amaan Khan\n\nSUPERVISOR:\n Levent Tuncel\n\nLOCAT
 ION: \n MC 5479\n\nABSTRACT: \n\nSecond-order Interior Point Methods (IP
 M) have been studied\nextensively over the past 80 years\, proving effecti
 ve for conic\noptimization. They can produce high-precision approximate so
 lutions in\nfew iterations. Each iteration is computationally expensive: T
 he core\nof each iteration is a large matrix inversion that scales poorly 
 with\nthe number of variables.\n\nIn large-scale applications\, we cannot 
 bear the per-iteration cost\n(perhaps due to lack of memory)\, so we inste
 ad turn to first-order\nmethods. We study a first-order IPM that uses a lo
 w-rank update scheme\nto replace the matrix inversion with significantly l
 ower per-iteration\ncost\, and compare this to other first-order methods f
 or solving LP at\nscale.
DTSTAMP:20260905T120324Z
END:VEVENT
BEGIN:VEVENT
UID:6a9c050cd1942
DTSTART;TZID=America/Toronto:20260806T130000
SEQUENCE:0
TRANSP:TRANSPARENT
DTEND;TZID=America/Toronto:20260806T160000
URL:https://uwaterloo.ca/combinatorics-and-optimization/events/phd-defense-
 leo-jung-preprocessing-hard-optimization
SUMMARY:PhD Defense - Leo Jung - Preprocessing for Hard Optimization Proble
 ms\nAcross Structurally Diverse Models
CLASS:PUBLIC
DESCRIPTION:SPEAKER:\n\nLeo Jung\n\nLOCATION:\n MC 5029\n\nABSTRACT: \n\nD
 ifficulties in solving large-scale optimization problems often arise\nfrom
  structural pathologies such as ill-conditioning\, Hadamard\nill-posedness
 \, and degeneracy\, particularly due to the failure of\nconstraint qualifi
 cations. While standard algorithms often struggle to\naddress these issues
 \, preprocessing based on structural analysis\noffers an effective strateg
 y for overcoming such challenges. This\nthesis investigates several prepro
 cessing methods targeting various\nsources of these difficulties. \nIn Par
 t I\, we study a nonclassical\, average condition number of linear\nsystem
 s\, the $\\omega$-condition number. Our results demonstrate\nseveral advan
 tages of the $\\omega$-condition number over the classical\n$\\kappa$-cond
 ition number. First\, $\\omega$ provides a more accurate\nmeasure of the c
 onditioning of linear systems by more faithfully\ncapturing the effects of
  perturbations observed in practice. Second\,\n$\\omega$ exhibits superior
  numerical stability compared to $\\kappa$.\nThird\, when used in precondi
 tioner design\, $\\omega$ more effectively\npromotes eigenvalue clustering
 \, which is crucial for the efficiency of\niterative solvers. Finally\, th
 e analytical simplicity of $\\omega$\nenables the derivation of explicit o
 ptimality conditions\, allowing for\nclosed-form expressions of optimal pr
 econditioners under various\nframeworks\, including low rank updates of th
 e generalized Jacobian for\nsemismooth Newton methods and diagonal or bloc
 k-diagonal scaling. For\ndiagonal preconditioning\, we further include a c
 omparison between two\ndistinct notions of conditioning. \nIn Part II\, we
  first answer in the affirmative a long-standing open\nquestion of whether
  the smooth stress function admits local nonglobal\nminimizers. This quart
 ic nonconvex objective function arises in the\nexact recovery of a Euclide
 an distance matrix (EDM) of a given\nembedding dimension. By eliminating t
 he Hadamard ill-posedness caused\nby translation and rotation invariance\,
  we stabilize Newton's method\nand avoid singular Hessians. \\\\ \nWe then
  consider the single-element error correction problem as a case\nstudy. We
  first show that the standard nearest EDM formulation based\non minimizing
  the smooth stress function fails to recover the correct\nEDM in this sett
 ing. We then introduce divide-and-conquer strategies\nbased on facial redu
 ction. Our approach efficiently recovers the\ncorrect EDM with high accura
 cy\, and we further provide criteria\ncharacterizing the existence of mult
 iple solutions. \nIn Part III\, we relate FR to the analysis of the conver
 gence behaviour\nof a semismooth Newton method for projection onto a spect
 rahedron\,\ni.e.\, the intersection of a linear manifold and the semidefin
 ite cone.\nIn this process\, we derive an explicit formula for the project
 ion onto\na face of the semidefinite cone obtained via regularization and\
 nanalyze pathologies that arise in the absence of strict feasibility.\nWe 
 further show that ill-conditioning of the Jacobian near optimality\ncharac
 terizes the degeneracy of the projection point. \\\\ \nAs an application\,
  we consider a simplified Wasserstein barycenter\nproblem\, a well-known N
 P-hard problem. We compute the Wasserstein\nbarycenter by exploiting the s
 tructure of the linear constraints to\nobtain a facially reduced doubly no
 nnegative (DNN) relaxation. This\nreduction provides a natural splitting f
 or applying the symmetric\nalternating direction method of multipliers (sA
 DMM). The resulting\nalgorithm exploits structure in the subproblems to co
 mpute strong\nupper and lower bounds. In most of the instances\, we achiev
 e the small\ngap between these bounds\, which means that the original prob
 lem is\nsolved.
DTSTAMP:20260905T120324Z
END:VEVENT
BEGIN:VEVENT
UID:6a9c050cd2b59
DTSTART;TZID=America/Toronto:20221028T090000
SEQUENCE:0
TRANSP:TRANSPARENT
DTEND;TZID=America/Toronto:20221029T170000
URL:https://uwaterloo.ca/combinatorics-and-optimization/events/workshop-lar
 ge-scale-optimization-and-applications
SUMMARY:Workshop on Large Scale Optimization and Applications
CLASS:PUBLIC
DESCRIPTION:Optimization is an important area of applied mathematics that b
 ridges\nmathematical theory with applications in diverse fields. This Twen
 ty\nFourth Annual Midwest Optimization Meeting provides opportunities for\
 nresearchers in this region with different backgrounds to come together\nt
 o share their research and teaching experiences\, forge collaborations\nwi
 th colleagues from different institutions\, and to expose students to\napp
 lications of mathematical theory. This workshop will focus on\nbringing t
 ogether several of the diverse communities working on large\nscale optimiz
 ation models that arise from variational problems.\n\nRegistration informa
 tion\, schedule\, and abstracts click here\n[https://www.math.uwaterloo.ca
 /~hwolkowi/Univ.Waterloo.24thMidwestOptimizationMeeting.html]
DTSTAMP:20260905T120324Z
END:VEVENT
BEGIN:VEVENT
UID:6a9c050cd3bcb
DTSTART;TZID=America/Toronto:20210719T161500
SEQUENCE:0
TRANSP:TRANSPARENT
DTEND;TZID=America/Toronto:20210719T161500
URL:https://uwaterloo.ca/combinatorics-and-optimization/events/special-siam
 -session-memoriam-tom-colemans-contributions
SUMMARY:Special SIAM Session - In Memoriam: Tom Coleman’s Contributions t
 o\nApplied Mathematics and Optimization
CLASS:PUBLIC
DESCRIPTION:TITLE: In Memoriam: Tom Coleman’s Contributions to Applied\n
 Mathematics and Optimization\n\nSpeakers:\n\nYuying Li\, Stephen Wright\, 
 Alex Pothen\, Bruce Hendrickson\, Peter\nForsyth\, and Somayeh Moazeni\n\n
 Affiliation:\n\nSIAM Annual Meeting (AN21)\n\nRegistration:\n https://www.
 siam.org/conferences/cm/conference/an21\n\nDESCRIPTION:\n\nThomas F. Colem
 an—a leader in optimization and scientific computing\,\nprofessor at the
  University of Waterloo\, and a SIAM Fellow—passed\naway on April 20\, 2
 021. Tom served as the Director of the Theory\nCenter at Cornell and then 
 as Dean of the Faculty of Mathematics at\nthe University of Waterloo. His 
 research spanned continuous\noptimization\, combinatorial scientific compu
 ting\, automatic\ndifferentiation\, financial optimization\, mathematical 
 software\, etc.\nIn this session\, his wife and collaborator\, Yuying Li\,
  and five of his\nstudents and colleagues will describe the pioneering con
 tributions\nthat Tom made to these fields in his research.
DTSTAMP:20260905T120324Z
END:VEVENT
BEGIN:VEVENT
UID:6a9c050cd46f1
DTSTART;TZID=America/Toronto:20181127T173000
SEQUENCE:0
TRANSP:TRANSPARENT
DTEND;TZID=America/Toronto:20181127T173000
URL:https://uwaterloo.ca/combinatorics-and-optimization/events/cryptoworks2
 1-distinguished-lecture-marc-morin
LOCATION:QNC - Quantum Nano Centre 200 University Avenue West 0101 Waterloo
  ON N2L 3G1 Canada
SUMMARY:CryptoWorks21 Distinguished Lecture - Marc Morin
CLASS:PUBLIC
DESCRIPTION:THE \"BLOOD\, SWEAT\, TEARS\, TOIL AND TRIUMPHS\" OF COMMERCIAL
 IZING\nTECHNOLOGY\n\nMARC MORIN is the co-founder and CEO of Auvik Network
 s\, creators of\ncloud-based software that makes it dramatically easier fo
 r IT managed\nservice providers to monitor and manage their clients' IT ne
 tworks. A\nserial entrepreneur\, Marc has previously co-founded several su
 ccessful\ncompanies\, including PixStream (acquired by Cisco for USD$369 m
 illion)\nand Sandvine (Sold to Francisco Partners for CAD$582 million)\, a
 nd is\na seed investor in a number of local tech companies.
DTSTAMP:20260905T120324Z
END:VEVENT
BEGIN:VEVENT
UID:6a9c050cd54d5
DTSTART;TZID=America/Toronto:20180705T153000
SEQUENCE:0
TRANSP:TRANSPARENT
DTEND;TZID=America/Toronto:20180705T153000
URL:https://uwaterloo.ca/combinatorics-and-optimization/events/graphs-and-m
 atroids-seminar-5
LOCATION:MC - Mathematics & Computer Building 200 University Avenue West 54
 79 Waterloo ON N2L 3G1 Canada
SUMMARY:Graphs and Matroids Seminar
CLASS:PUBLIC
DESCRIPTION:TITLE:Generalizing the problem of packing disjoint cycles\n\nSp
 eaker:\n Paul Wollan\n\nAffiliation:\n University of Rome \"La Sapienza\"\
 n\nRoom:\n MC 5479\n\nABSTRACT: A classic result of Erdos and Posa states
  that there exists\na function f such that for all k\,
DTSTAMP:20260905T120324Z
END:VEVENT
BEGIN:VEVENT
UID:6a9c050cd6229
DTSTART;TZID=America/Toronto:20150915T113000
SEQUENCE:0
TRANSP:TRANSPARENT
DTEND;TZID=America/Toronto:20150915T130000
URL:https://uwaterloo.ca/combinatorics-and-optimization/events/grad-social
LOCATION:MC 200 University Avenue West 5501 Waterloo ON N2L 3G1 Canada
SUMMARY:Grad Social
CLASS:PUBLIC
DTSTAMP:20260905T120324Z
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