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DTSTART:20190331T010000
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DTSTART:20191027T010000
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DTSTART;TZID=Europe/Helsinki:20190916T110000
DTEND;TZID=Europe/Helsinki:20190916T120000
DTSTAMP:20260818T220629
CREATED:20190827T144833Z
LAST-MODIFIED:20190827T144833Z
UID:12311-1568631600-1568635200@crest.science
SUMMARY:Julien Combe : "Unpaired Kidney Exchange: Overcoming Double Coincidence of Wants without Money"
DESCRIPTION:CREST Internal Seminar in Microeconomics :  \n\nPlace: Room 3105\n  \nAbstract: We propose a new matching algorithm—Unpaired kidney exchange—to tackle the problem of double coincidence of wants without using money. The fundamental idea is that “memory” can serve as a medium of exchange. In a dynamic matching model with heterogeneous agents\, we prove that average waiting time under the Unpaired algorithm is close-to optimal\, and substantially less than the standard pairwise and chain exchange algorithms. We evaluate this algorithm using a rich dataset of the kidney patients in France. Counterfactual simulations show that the Unpaired algorithm can match nearly 57% of the patients\, with an average waiting time of 424 days (state-of-the-art algorithms match about 31% with an average waiting time of 675 days or more). The optimal algorithm performs only slightly better: it matches 58% of the patients and leads to an average waiting time of 410 days. The Unpaired algorithm confronts two incentive-related practical challenges. We address those challenges via a practical version of the Unpaired algorithm that employs kidneys from the deceased donors waiting list. The practical version can match nearly 87% of patient-donor pairs\, while reducing the average waiting time to about 141 days. \n\n\n\nOrganizers:\nAlexis Larousse (CREST)\nSponsors:\nCREST\n\n  \n
URL:https://crest.science/event/julien-combe-unpaired-kidney-exchange-overcoming-double-coincidence-of-wants-without-money/
LOCATION:3105
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DTSTART;TZID=Europe/Paris:20190916T140000
DTEND;TZID=Europe/Paris:20190916T151500
DTSTAMP:20260818T220629
CREATED:20190627T090506Z
LAST-MODIFIED:20190627T090506Z
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SUMMARY:Yuri POLYANSKI (MIT) - "Smoothed Empirical Measures and Entropy Estimation"
DESCRIPTION:\nThe Statistical Seminar: Every Monday at 2:00 pm.\nTime: 2:00 pm – 3:15 pm\nDate: 16th of September 2019\nPlace: Room 3001.\nYuri POLYANSKI (MIT) – “Smoothed Empirical Measures and Entropy Estimation“ \nAbstract: In this talk we discuss behavior of the empirical measure P_n corresponding to iid samples from a distribution P on a d-dimensional space. Let Q_n and Q denote the result of convolving P_n and P\, respectively\, with an isotropic standard Guassian kernel. We discuss convergence of the p-Wasserstein\, KL and other distances between Q_n and Q. Curiously\, for some distances (like 1-Wasserstein) we get parametric 1/sqrt(n) speed of convergence regardless of dimension\, whereas for some other distances (like 2-Wasserstein) the 1/sqrt(n) rate can change to \omega(1/sqrt(n)). We give an if and only if characterization in the class of subgaussian P for the parametric rate. As an application\, we show that differential entropy of Q_n converges to that of Q at parametric rate 1/sqrt(n) regardless of dimension. An estimator of differential entropy of Q\, in turn\, allows us to estimate the input-output mutual information in noisy neural networks. \nJoint work with Ziv Goldfeld\, Kristjan Greenewald and Jonathan Weed.\nOrganizers:\nCristina BUTUCEA\, Alexandre TSYBAKOV\, Julie JOSSE\, Eric MOULINES\, Mathieu ROSENBAUM\nSponsors:\nCREST-CMAP\n \n\n
URL:https://crest.science/event/yuri-polyanski/
CATEGORIES:Statistics
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