Tootfinder

Anticipating early 2026 opening, Oregon seeks to block potential Newport ICE facility • Washington State Standard
https://washingtonstatestandard.com/2025/12/22/repub/anticipating-early-2026-opening-oregon-seeks-to-block-potential-newport-ice-facility/

🇺🇦 #NowPlaying on KEXP's #Continent
Rorystonelove Ft Samori I:
🎵 Lost Africans
#RorystoneloveFtSamoriI
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https://open.spotify.com/track/1Nn4VRdLuVfZdc33mGNZCB

Ciężko mi się czyta artykuły z oko.press. Naprawdę nie wiem, skąd tyle literówek i drastycznych błędów redakcyjnych. To wygląda jak pisane w pośpiechu na telefonie.

Federated Learning in the Wild: A Comparative Study for Cybersecurity under Non-IID and Unbalanced Settings
Roberto Doriguzzi-Corin, Petr Sabel, Silvio Cretti, Silvio Ranise
https://arxiv.org/abs/2509.17836

Federated Learning in the Wild: A Comparative Study for Cybersecurity under Non-IID and Unbalanced Settings
Machine Learning (ML) techniques have shown strong potential for network traffic analysis; however, their effectiveness depends on access to representative, up-to-date datasets, which is limited in cybersecurity due to privacy and data-sharing restrictions. To address this challenge, Federated Learning (FL) has recently emerged as a novel paradigm that enables collaborative training of ML models across multiple clients while ensuring that sensitive data remains local. Nevertheless, Federated Av…

End-to-end RL Improves Dexterous Grasping Policies
Ritvik Singh, Karl Van Wyk, Pieter Abbeel, Jitendra Malik, Nathan Ratliff, Ankur Handa
https://arxiv.org/abs/2509.16434 https:…

End-to-end RL Improves Dexterous Grasping Policies
This work explores techniques to scale up image-based end-to-end learning for dexterous grasping with an arm + hand system. Unlike state-based RL, vision-based RL is much more memory inefficient, resulting in relatively low batch sizes, which is not amenable for algorithms like PPO. Nevertheless, it is still an attractive method as unlike the more commonly used techniques which distill state-based policies into vision networks, end-to-end RL can allow for emergent active vision behaviors. We id…

RelRepair: Enhancing Automated Program Repair by Retrieving Relevant Code
Shunyu Liu, Guangdong Bai, Mark Utting, Guowei Yang
https://arxiv.org/abs/2509.16701 https://

RelRepair: Enhancing Automated Program Repair by Retrieving Relevant Code
Automated Program Repair (APR) has emerged as a promising paradigm for reducing debugging time and improving the overall efficiency of software development. Recent advances in Large Language Models (LLMs) have demonstrated their potential for automated bug fixing and other software engineering tasks. Nevertheless, the general-purpose nature of LLM pre-training means these models often lack the capacity to perform project-specific repairs, which require understanding of domain-specific identifie…

@… Right. Since we already had “scientists” cranking out a hundred papers per year, the uptake of #genAI was inevitable. In some respects it has just accelerated a process that had already been underway.
But it’s nevertheless shocking.

@… Right. Since we already had “scientists” cranking out a hundred papers per year, the uptake of #genAI was inevitable. In some respects it has just accelerated a process that had already been underway.
But it’s nevertheless shocking.

Minimization of Nonsmooth Weakly Convex Function over Prox-regular Set for Robust Low-rank Matrix Recovery
Keita Kume, Isao Yamada
https://arxiv.org/abs/2509.17549 https://

Minimization of Nonsmooth Weakly Convex Function over Prox-regular Set for Robust Low-rank Matrix Recovery
We propose a prox-regular-type low-rank constrained nonconvex nonsmooth optimization model for Robust Low-Rank Matrix Recovery (RLRMR), i.e., estimate problem of low-rank matrix from an observed signal corrupted by outliers. For RLRMR, the $\ell_{1}$-norm has been utilized as a convex loss to detect outliers as well as to keep tractability of optimization models. Nevertheless, the $\ell_{1}$-norm is not necessarily an ideal robust loss because the $\ell_{1}$-norm tends to overpenalize entries c…

This weekend I visited some boomer relatives who told me that the dodgy Fire stick they bought from a man down the pub stopped working and "wouldn't update". The man down the pub said "probably your TV is too old", so they bought a new TV.
Dodgy Fire stick still doesn't work, you will be unsurprised to learn.
Nevertheless, a welcome bit of mirth amongst their other news that 20 year old illegal immigrants are attending UK secondary schools, and there&#…