Tootfinder

Interessante Betrachtung: was wäre Eigentum - bei manchen Männern, die die Welt verbrennen, höher im Wert als Benzin oder unsere Verfassung - wert, wenn es nicht durch menschgemachte Klimakatastrophen bedroht wäre.
From: @…

Post by AJ Sadauskas, @aj@gts.sadauskas.id.au
New research shows the economic impact of increased flooding from global warming from fossil fuel pollution. Properties in Australia's flood-prone areas are worth $42 billion less than they would be if they weren't in a flood-prone area. https://www.sbs.com.au/news/article/homeowners-flood-4...

The US v. Google ad tech trial, in which a judge ruled that the company illegally monopolized the digital ad market, begins its remedies phase (Digiday)
https://digiday.com/media-buying/everything-you-need-to-know-abou…

Everything you need to know about the closing stages of Google’s ad tech antitrust trial
The arguments, witnesses and timelines involved in the Google antirust trial that could see the biggest company in advertising broken up.

Texans' D thumps Bills, stakes claim as NFL's best https://www.espn.com/nfl/story/_/id/47045167/texans-defense-thumps-bills-stakes-claim-league-best

from my link log —
Seven stages of open software.
https://coiled.io/blog/stages-of-openness.html
saved 2020-03-29 https://dotat.a…

The US v. Google ad tech trial, in which a judge ruled that the company illegally monopolized the digital ad market, begins its remedies phase (Digiday)
https://digiday.com/media-buying/everything-you-need-to-know-abou…

Everything you need to know about the closing stages of Google’s ad tech antitrust trial
The arguments, witnesses and timelines involved in the Google antirust trial that could see the biggest company in advertising broken up.

Uniqueness of inverse random source problems for stochastic heat and wave equations
Xu Wang, Guanlin Yang, Zhidong Zhang
https://arxiv.org/abs/2509.15928 https://

Uniqueness of inverse random source problems for stochastic heat and wave equations
This paper investigates an inverse random source problem for stochastic evolution equations, including stochastic heat and wave equations, with the unknown source modeled as $g(x)f(t)\dot{W}(t)$. The research commences with the establishment of the well-posedness of the corresponding stochastic direct problem. Under suitable regularity conditions, the existence of stochastic strong solutions for both the stochastic heat and wave equations is demonstrated. For the inverse problem, the objective …

🇺🇦 #NowPlaying on KEXP's #MorningShow
Iggy and The Stooges:
🎵 Search and Destroy
#IggyandTheStooges
https://bastardon.bandcamp.com/track/search-and-destroy-iggy-and-the-stooges
https://open.spotify.com/track/00sydAz6PeOxYzwG1dRIPi

Volgens mij had ik nog niet gemeld dat ik omgekeerde-frambozen-polentakoek heb gebakken. Ik moet nu een randje proeven, anders kan de taartdoos niet dicht.

Phase Transition for Stochastic Block Model with more than $\sqrt{n}$ Communities
Alexandra Carpentier, Christophe Giraud, Nicolas Verzelen
https://arxiv.org/abs/2509.15822 http…

Phase Transition for Stochastic Block Model with more than $\sqrt{n}$ Communities
Predictions from statistical physics postulate that recovery of the communities in Stochastic Block Model (SBM) is possible in polynomial time above, and only above, the Kesten-Stigum (KS) threshold. This conjecture has given rise to a rich literature, proving that non-trivial community recovery is indeed possible in SBM above the KS threshold, as long as the number $K$ of communities remains smaller than $\sqrt{n}$, where $n$ is the number of nodes in the observed graph. Failure of low-degree …

SETrLUSI: Stochastic Ensemble Multi-Source Transfer Learning Using Statistical Invariant
Chunna Li, Yiwei Song, Yuanhai Shao
https://arxiv.org/abs/2509.15593 https://

SETrLUSI: Stochastic Ensemble Multi-Source Transfer Learning Using Statistical Invariant
In transfer learning, a source domain often carries diverse knowledge, and different domains usually emphasize different types of knowledge. Different from handling only a single type of knowledge from all domains in traditional transfer learning methods, we introduce an ensemble learning framework with a weak mode of convergence in the form of Statistical Invariant (SI) for multi-source transfer learning, formulated as Stochastic Ensemble Multi-Source Transfer Learning Using Statistical Invari…