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DTSTART;TZID=America/Los_Angeles:20260501T161500
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CREATED:20260426T200817Z
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SUMMARY:An Exact Algorithm for the Unanimous Vote Problem (Feyza Duman Keles\, NYU)
DESCRIPTION:Abstract: Consider n independent\, biased coins\, each with a known probability of heads. Presented with an ordering of these coins\, flip (i.e.\, toss) each coin once\, in that order\, until we have observed both a head and a tail\, or flipped all coins. The Unanimous Vote problem asks us to find the ordering that minimizes the expected number of flips. Gkenosis et al. [arXiv:1806.10660] gave a polynomial-time approximation algorithm for this problem\, where the approximation ratio is the golden ratio. They left open whether the problem was NP-hard. We answer this question by giving an exact algorithm that runs in time O(n log n). The Unanimous Vote problem is an instance of the more general Stochastic Boolean Function Evaluation problem: it thus becomes one of the only such problems known to be solvable in polynomial time. Our proof uses simple interchange arguments to show that the optimal ordering must be close to the ordering produced by a natural greedy algorithm. Beyond our main result\, we compare the optimal ordering with the best adaptive strategy\, proving a tight adaptivity gap of 1.2 + o(1) for the Unanimous Vote problem.
URL:https://colleges.claremont.edu/ccms/event/an-exact-algorithm-for-the-unanimous-vote-problem-feyza-duman-keles-nyu/
LOCATION:Emmy Noether Room\, Estella 1021\, Pomona College\,\, 610 N. College Ave.\, Claremont\, CA\, 91711\, United States
CATEGORIES:Analysis Seminar
ORGANIZER;CN="Ryan Aschoff":MAILTO:ryan.aschoff@cgu.edu
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DTSTART;TZID=America/Los_Angeles:20260505T121500
DTEND;TZID=America/Los_Angeles:20260505T131000
DTSTAMP:20260522T025809
CREATED:20260119T224840Z
LAST-MODIFIED:20260427T163251Z
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SUMMARY:Voting on relations using pairs information (Michael Orrison\, HMC)
DESCRIPTION:Many aggregation problems ask us to turn individual judgments into a single collective outcome. In this talk\, we model each voter’s input as a relation on a set of alternatives\, allowing pairwise comparisons to include strict preferences\, ties\, or incomparability. This perspective gives a common framework for median procedures and scoring methods\, including several familiar voting rules. The distance-based side leads naturally to graphs such as the hypercube of relations\, while the scoring-based side leads to questions about linear operators on functions on relations. At the center is a natural four-parameter family of scoring matrices whose eigenspace decompositions separate meaningful types of pairwise information\, connecting voting theory with graph theory\, linear algebra\, and harmonic analysis. \nThis is joint work with Karl-Dieter Crisman\, Erin McNicholas\, and Kathryn Nyman.
URL:https://colleges.claremont.edu/ccms/event/antc-talk-michael-orrison-hmc/
LOCATION:Estella 2099
CATEGORIES:Algebra / Number Theory / Combinatorics Seminar
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DTSTART;TZID=America/Los_Angeles:20260519T113000
DTEND;TZID=America/Los_Angeles:20260519T123000
DTSTAMP:20260522T025809
CREATED:20260515T021837Z
LAST-MODIFIED:20260515T022232Z
UID:4097-1779190200-1779193800@colleges.claremont.edu
SUMMARY:Unraveling Hidden Patterns with Topological Data Analysis (Dr. Elena Wang\, University of Fribourg\, Switzerland)
DESCRIPTION:Topology\, akin to geometry\, delves into the study of the shapes and structures of mathematical spaces\, ranging from simple surfaces to intricate collections of functions and objects. In recent years\, these foundational concepts have extended beyond pure mathematics to address practical problems in data science\, influencing diverse areas such as chemistry\, neuroscience\, and robotics. This talk aims to demystify the core techniques of Topological Data Analysis (TDA)\, such as persistent homology\, and illustrate their significance through applications in shape analysis\, machine learning\, and computational biology. We will explore how TDA provides unique insights into data structuring and analysis\, offering solutions to complex problems. \nPizza will be served.
URL:https://colleges.claremont.edu/ccms/event/unraveling-hidden-patterns-with-topological-data-analysis-dr-elena-wang-university-of-fribourg-switzerland/
LOCATION:Estella 2099\, Pomona College\, 610 N. College Ave.\, Claremont\, CA\, United States
CATEGORIES:Topology Seminar
ORGANIZER;CN="Vin de Silva":MAILTO:vin.desilva@pomona.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260908T121500
DTEND;TZID=America/Los_Angeles:20260908T131000
DTSTAMP:20260522T025809
CREATED:20260417T223051Z
LAST-MODIFIED:20260417T223051Z
UID:4081-1788869700-1788873000@colleges.claremont.edu
SUMMARY:ANTC talk -- Michelle Manes (American Institute of Mathematics)
DESCRIPTION:
URL:https://colleges.claremont.edu/ccms/event/antc-talk-michelle-manes-american-institute-of-mathematics/
LOCATION:TBA
CATEGORIES:Algebra / Number Theory / Combinatorics Seminar
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