Tootfinder

Ok, this is pretty awesome. Quite a nifty way to solve the problem of visibility of small fediverse instances. https://gts.sadauskas.id.au/@aj/statuses/01JS8ZXQ41B1ZH33AZ2R2XGY2Y

Post by AJ Sadauskas, @aj@gts.sadauskas.id.au
I've got a quick favour to ask. If you're reading this post on Mastodon (or the Fediverse), please click boost. How come? I recently moved across to my own self-hosted single-user server (using GoToSocial.org). For a bunch of reasons, including visibility across the Fedi, it would really hel...

RFK Jr.'s vaccine pullback stokes fears of lost medical breakthroughs (Maya Goldman/Axios)
https://www.axios.com/2025/08/10/rfk-jrs-vaccine-pullback-stokes-fears-of-lost-medical-breakthroughs
http://www.memeorandum.com/250810/p25#a250810p25

Stochastic Alignments: Matching an Observed Trace to Stochastic Process Models
Tian Li, Artem Polyvyanyy, Sander J. J. Leemans
https://arxiv.org/abs/2507.06472

Stochastic Alignments: Matching an Observed Trace to Stochastic Process Models
Process mining leverages event data extracted from IT systems to generate insights into the business processes of organizations. Such insights benefit from explicitly considering the frequency of behavior in business processes, which is captured by stochastic process models. Given an observed trace and a stochastic process model, conventional alignment-based conformance checking techniques face a fundamental limitation: They prioritize matching the trace to a model path with minimal deviations,…

An overlapping domain decomposition method for parametric Stokes and Stokes-Darcy problems via proper generalized decomposition
Marco Discacciati, Ben J. Evans, Matteo Giacomini
https://arxiv.org/abs/2507.06861

An overlapping domain decomposition method for parametric Stokes and Stokes-Darcy problems via proper generalized decomposition
A strategy to construct physics-based local surrogate models for parametric Stokes flows and coupled Stokes-Darcy systems is presented. The methodology relies on the proper generalized decomposition (PGD) method to reduce the dimensionality of the parametric flow fields and on an overlapping domain decomposition (DD) paradigm to reduce the number of globally coupled degrees of freedom in space. The DD-PGD approach provides a non-intrusive framework in which end-users only need access to the mat…

Stochastic Quadratic Dynamic Programming
Vincent Guigues, Adriana Washington
https://arxiv.org/abs/2506.07314 https://arxiv.org/pdf/2…

Stochastic Quadratic Dynamic Programming
We introduce an algorithm called SQDP (Stochastic Quadratic Dynamic Programming) to solve some multistage stochastic optimization problems having strongly convex recourse functions. The algorithm extends the classical Stochastic Dual Dynamic Programming (SDDP) method replacing affine cuts by quadratic cuts. We provide conditions ensuring strong convexity of the recourse functions and prove the convergence of SQDP. In the special case of a single stage deterministic problem, we call QCSC (Quadra…

Master equations for continuous-time random walks with stochastic resetting
Fausto Colantoni, Gianni Pagnini
https://arxiv.org/abs/2507.07590 https://

Master equations for continuous-time random walks with stochastic resetting
We study a general continuous-time random walk (CTRW), by including non-Markovian cases and Lévy flights, under complete stochastic resetting to the initial position with an arbitrary law, which can be power-lawed as well as Poissonian. We provide three linked results. First, we show that the random walk under stochastic resetting is a CTRW with the same jump-size distribution of the non-reset original CTRW but different counting process. Later, we derive the condition for a CTRW with stochast…

Nvidia says its GPUs do not contain backdoors, kill switches, or spyware, and hard-coded, single-point controls like kill switches undermine trust in US tech (David Reber Jr/NVIDIA)
https://blogs.nvidia.com/blog/no-backdoors-no-kill-switches-no-spyware/

No Backdoors. No Kill Switches. No Spyware.
To mitigate the risk of misuse, some pundits and policymakers propose requiring hardware “kill switches” or built-in controls that can remotely disable GPUs without user knowledge and consent. Some suspect they might already exist. NVIDIA GPUs do not and should not have kill switches and backdoors.

It's hard to know who to be sorrier for. The 9,000 who are losing their jobs, or the rest who are going to have to take on not only the additional work of clearing up the mess the AI makes, but also the work of their dismissed colleagues.
#Microsoft
#StochasticParrots
…

Microsoft to cut up to 9,000 jobs as it invests in AI
The US tech giant will axe 4% of its global workforce and plough money into artificial intelligence.

Fractional Programming for Stochastic Precoding over Generalized Fading Channels
Wenyu Wang, Kaiming Shen
https://arxiv.org/abs/2507.06944 https://

Fractional Programming for Stochastic Precoding over Generalized Fading Channels
This paper seeks an efficient algorithm for stochastic precoding to maximize the long-term average weighted sum rates throughout a multiple-input multiple-output (MIMO) network. Unlike many existing works that assume a particular probability distribution model for fading channels (which is typically Gaussian), our approach merely relies on the first and second moments of fading channels. For the stochastic precoding problem, a naive idea is to directly apply the fractional programming (FP) meth…

Efficient Stochastic BFGS methods Inspired by Bayesian Principles
Andr\'e Carlon, Luis Espath, Ra\'ul Tempone
https://arxiv.org/abs/2507.07729 http…

Efficient Stochastic BFGS methods Inspired by Bayesian Principles
Quasi-Newton methods are ubiquitous in deterministic local search due to their efficiency and low computational cost. This class of methods uses the history of gradient evaluations to approximate second-order derivatives. However, only noisy gradient observations are accessible in stochastic optimization; thus, deriving quasi-Newton methods in this setting is challenging. Although most existing quasi-Newton methods for stochastic optimization rely on deterministic equations that are modified to…