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X-WR-CALDESC:Events for CREST
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TZID:Europe/Helsinki
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DTSTART:20230326T010000
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DTSTART:20231029T010000
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DTSTART;TZID=Europe/Helsinki:20231002T121500
DTEND;TZID=Europe/Helsinki:20231002T133000
DTSTAMP:20260723T200742
CREATED:20230621T035436Z
LAST-MODIFIED:20230905T120920Z
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SUMMARY:Francisco RUGE-MURCIA (Mc Gill) "Relative Price Shocks and Inflation"
DESCRIPTION:The Macro Seminar:\nTime: 12:15 pm – 13:30 pm\nDate: 02th of October 2023 \nRoom 3001 \nFrancisco RUGE-MURCIA (Mc Gill) “Relative Price Shocks and Inflation” \nAbstract : Inflation is determined by interaction between real factors and monetary policy. Among the most important real factors are shocks to the supply and demand for different components of the consumption basket. We use an estimated multi-sector New Keynesian model to decompose the behavior of U.S. inflation into contributions from sectoral (or “relative price”) shocks\, monetary policy shocks\, and aggregate real shocks. The model is estimated by maximum likelihood with U.S. data for the post-1994 period in which inflation and the monetary policy regime appeared to be stable. In addition to providing a broad decomposition of inflation behavior\, we enlist the model to help us understand the inflation shortfall from 2012 to 2019\, and the dramatic inflation movements during the COVID pandemic. \nSponsors:\nAlessandro RIBONI (CREST) \n
URL:https://crest.science/event/francisco-ruge-murcia-mc-gill-t-b-a/
CATEGORIES:Macroeconomics,Seminars
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DTSTART;TZID=Europe/Helsinki:20231002T140000
DTEND;TZID=Europe/Helsinki:20231002T151500
DTSTAMP:20260723T200742
CREATED:20230926T042018Z
LAST-MODIFIED:20230926T042018Z
UID:16004-1696255200-1696259700@crest.science
SUMMARY:Anna KORBA (CREST) - Sampling with Mollified Interaction Energy Descent
DESCRIPTION:Statistical Seminar: Every Monday at 2:00 pm.\nTime: 2:00 pm – 3:15 pm\nDate: 2nd october 2023\nPlace : 3001 \n  \nAnna KORBA – Sampling with Mollified Interaction Energy Descent \n  \n  \nAbstract: \n  \nSampling from a target measure whose density is only known up to a normalization constant is a fundamental problem in computational statistics and machine learning. We present a new optimization-based method for sampling called mollified interaction energy descent (MIED)\, that minimizes an energy on probability measures called mollified interaction energie (MIE). The latter converges to the chi-square divergence with respect to the target measure and the gradient flow of the MIE agrees with that of the chi-square divergence\, as the mollifiers approach Dirac deltas. Optimizing this energy with proper discretization yields a practical first-order particle-based algorithm for sampling in both unconstrained and constrained domains. We show the performance of our algorithm on both unconstrained and constrained sampling in comparison to state-of-the-art alternatives. \n  \nOrganizers:\nCristina BUTUCEA (CREST)\, Alexandre TSYBAKOV (CREST)\, Karim LOUNICI (CMAP) \, Jaouad MOURTADA (CREST)\nSponsors:\nCREST-CMAP \n
URL:https://crest.science/event/anna-korba-crest-sampling-with-mollified-interaction-energy-descent/
CATEGORIES:Statistics
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