Tootfinder

En Birmanie, la guerre recomposée par Pékin dans l’Etat Shan
https://www.lemonde.fr/international/article/2026/06/14/en-birmanie-la-guerre-recomposee-par-pekin-dans-l-etat-shan_6702232_3210.html…

En Birmanie, la guerre recomposée par Pékin dans l’Etat Shan
La Chine a stoppé l’avancée de la rébellion dans l’Etat Shan pour sauver une junte chancelante et rouvrir son projet de corridor économique, du Yunnan jusqu’à l’océan Indien. Pour Pékin, cet axe est une assurance-vie stratégique en cas de crise autour de Taïwan. Pour la Birmanie, il signifie une dépendance accrue à son puissant voisin et un redécoupage du champ de bataille, où armées, groupes ethniques et civils doivent désormais composer avec la « pax sinica ».

'Significant change' needed to tackle agri pollution #environment

'Significant change' needed to tackle agri pollution
The Office for Environmental Protection said existing regulations are insufficient to deliver necessary water quality improvements.

Let me get this straight. Xbox leadership believes the way to winning back people with great exclusives is by firing the people who make them — the people whose expertise they already paid billions to acquire? Sure. Seems really smart! https://www.eurogamer.net/xbox-layoffs-business-reset

312 GitHub contributions so far this year, Chicago represent! Would be significantly more, if I wouldn't ship to repos on Azure...

Improved Approximation Guarantees for Groupwise Maximin Share Fairness
Georgios Amanatidis, Anna Korfiati, Evangelos Markakis, Christodoulos Santorinaios
https://arxiv.org/abs/2606.04731 https://arxiv.org/pdf/2606.04731 https://arxiv.org/html/2606.04731
arXiv:2606.04731v1 Announce Type: new
Abstract: We study the problem of fairly allocating a set of indivisible goods to a set of $n$ agents with additive valuation functions. We focus on the very demanding notion of \textit{groupwise maximin share fairness} (GMMS), which requires that each agent $i$ receives value comparable to their maximin share, where the latter is computed \textit{with respect to any subset of agents that contains $i$}. We show that it is possible to compute $(\phi-1)$-approximate GMMS allocations in polynomial time, where $\phi \approx 1.618$ is the golden ratio). This improves on the previously known guarantee of $4/7$ of Chaudhury et al. [SICOMP; 2021] and Amanatidis et al. [TCS; 2020]. We propose a simple algorithm that maintains the same main properties as the Draft-and-Eliminate algorithm of Amanatidis et al. [TCS, 2020] and we improve on the approximation guarantee analysis by carefully bounding the relevant value within any subinstance induced by the restriction of our allocation to a subset of agents. Our analysis is asymptotically tight for algorithms that share these properties and has the additional benefit of giving improved guarantees for restricted settings; in particular, when the agents agree on the top $n$ goods or when the number of agents is small. To illustrate the challenges of going beyond the guarantees of our algorithm, we also present a variant with an improved approximation of $(\sqrt{10}-1)/3 \approx 0.72$ for the case of three agents. To achieve this improvement we partially characterize the maximin share guarantees of short picking sequences for a small number of goods.
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