Cowboys playoff odds hinge on beating Lions, vanquishing road demons https://cowboyswire.usatoday.com/story/sports/nfl/cowboys/2025/12/04/cowboys-playoff-odds-detroit-lions-week-14-2025/87594898007/
Sources detail how Canadian media company Valnet gutted Military.com, including layoffs and a reduction of in-depth journalism, while facing new Pentagon rules (Liam Scott/Columbia Journalism Review)
https://www.cjr.org/feature/military-dot-c…
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Felix Mendelssohn & Van Kuijk Quartet:
🎵 String Quartet No 1 in E flat major, Op 12
#FelixMendelssohn #VanKuijkQuartet
https://open.spotify.com/track/7GwiFBnDHpVE2HUGxeKpOl
A look at the state of independent media in Myanmar, which lost US and Swedish funding this year and where subscriptions aren't a dependable source of revenue (Lorcan Lovett/Nieman Reports)
https://niemanreports.org/myanmar-independent-media-innova…
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Jahcoozi:
🎵 Sit & chuckle
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https://open.spotify.com/track/06vMxYCyobHsLjDTVANLuN
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Felix Mendelssohn & Van Kuijk Quartet:
🎵 String Quartet No. 6 in F Minor, Op. 80: III. Adagio
#FelixMendelssohn #VanKuijkQuartet
https://open.spotify.com/track/3MYvIo8iTv8BG0Fb2gjbUt
Robust forecast aggregation via additional queries
Rafael Frongillo, Mary Monroe, Eric Neyman, Bo Waggoner
https://arxiv.org/abs/2512.05271 https://arxiv.org/pdf/2512.05271 https://arxiv.org/html/2512.05271
arXiv:2512.05271v1 Announce Type: new
Abstract: We study the problem of robust forecast aggregation: combining expert forecasts with provable accuracy guarantees compared to the best possible aggregation of the underlying information. Prior work shows strong impossibility results, e.g. that even under natural assumptions, no aggregation of the experts' individual forecasts can outperform simply following a random expert (Neyman and Roughgarden, 2022).
In this paper, we introduce a more general framework that allows the principal to elicit richer information from experts through structured queries. Our framework ensures that experts will truthfully report their underlying beliefs, and also enables us to define notions of complexity over the difficulty of asking these queries. Under a general model of independent but overlapping expert signals, we show that optimal aggregation is achievable in the worst case with each complexity measure bounded above by the number of agents $n$. We further establish tight tradeoffs between accuracy and query complexity: aggregation error decreases linearly with the number of queries, and vanishes when the "order of reasoning" and number of agents relevant to a query is $\omega(\sqrt{n})$. These results demonstrate that modest extensions to the space of expert queries dramatically strengthen the power of robust forecast aggregation. We therefore expect that our new query framework will open up a fruitful line of research in this area.
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Antonín Dvořšk, Sol Gabetta, Danish National Symphony Orchestra & Mario Venzago:
🎵 Rondo in G Minor, Op.94
#AntonínDvořák #SolGabetta #DanishNationalSymphonyOrchestra #MarioVenzago
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Wolfgang Amadeus Mozart, Julian Bliss, Royal Northern Sinfonia & Mario Venzago:
🎵 Clarinet Concerto in A Major K.622 (3rd mvt)
#WolfgangAmadeusMozart #JulianBliss
https://open.spotify.com/track/07QAyyn7qFsWRzXcm2ddYk