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@NFL@darktundra.xyz
2026-03-26 14:40:19

10 biggest questions after free agency but before the 2026 draft nfl.com/news/10-biggest-questi

The US supreme court has decided to hear arguments in a
climate accountability lawsuit,
marking the first time the high court has weighed in on such a case.
The decision could potentially hinder the wave of climate litigation the US has seen in recent years.
“It’s not a good sign,”
said Pat Parenteau, a professor of environmental law at Vermont Law and Graduate School.
The lawsuit in question was filed by the city of Boulder, Colorado, against two major o…

@Techmeme@techhub.social
2026-03-26 01:51:10

San Francisco has become a laboratory for police surveillance after early resistance; SFPD recorded 700 drone flights last month, up from 93 in February 2025 (Cyrus Farivar/The San Francisco Standard)
sfstandard.com/2026/03/25/sf-s

@Tupp_ed@mastodon.ie
2026-02-25 07:18:37

Senator Alice Mary Higgins asked the Chairman of Ireland’s new Internet regulator, the CnaM why his organisation didn’t take action against Grok generating CSAM under the Irish Online Safety Code.
Apparently, it didn’t appear to them to be a breach of the code.
What , then, is it good for?

@theodric@social.linux.pizza
2026-03-26 06:14:50

In the grand European tradition of asking the same question over and over until the correct answer is provided, Chat Control is back for another vote! fightchatcontrol.eu/?foo=bar

@AimeeMaroux@mastodon.social
2026-03-26 10:17:19
Content warning:

One of the great things about the city of #Hamburg, Germany, is that there is always something interesting going on, at least when I'm visiting 🥰
Tonight at 5:30pm there is a protest against sexualised violence at the town hall and a newcomer film festival at Zeise Kinos. I want to try and do both but I'll likely just catch the tail-end of the film festival if I go to the protest.…

@privacity@social.linux.pizza
2026-02-26 16:08:32

chatcontrol e oscuramento: la guerra alla crittografia è in aumento. A causa di una losca collaborazione tra Stati Uniti e Unione Europea.
Sorveglianza di massa statale
Dopo la denuncia di Snowden nel 2013, ampie porzioni di Internet sono diventate crittografate, consentendo comunicazioni private e sicure. Non tutti hanno accolto con favore questo cambiamento. In particolare, l'FBI e altre agenzie governative statunitensi hanno combattuto quella che viene spesso definita la &q…

@scott@carfree.city
2026-02-25 05:32:53

As an ethical AI user, I begin each session by asking the chatbot to give a stolen data acknowledgement. It is an important first step toward justice.

@arXiv_csLG_bot@mastoxiv.page
2026-02-25 10:45:01

Statistical Query Lower Bounds for Smoothed Agnostic Learning
Ilias Diakonikolas, Daniel M. Kane
arxiv.org/abs/2602.21191 arxiv.org/pdf/2602.21191 arxiv.org/html/2602.21191
arXiv:2602.21191v1 Announce Type: new
Abstract: We study the complexity of smoothed agnostic learning, recently introduced by~\cite{CKKMS24}, in which the learner competes with the best classifier in a target class under slight Gaussian perturbations of the inputs. Specifically, we focus on the prototypical task of agnostically learning halfspaces under subgaussian distributions in the smoothed model. The best known upper bound for this problem relies on $L_1$-polynomial regression and has complexity $d^{\tilde{O}(1/\sigma^2) \log(1/\epsilon)}$, where $\sigma$ is the smoothing parameter and $\epsilon$ is the excess error. Our main result is a Statistical Query (SQ) lower bound providing formal evidence that this upper bound is close to best possible. In more detail, we show that (even for Gaussian marginals) any SQ algorithm for smoothed agnostic learning of halfspaces requires complexity $d^{\Omega(1/\sigma^{2} \log(1/\epsilon))}$. This is the first non-trivial lower bound on the complexity of this task and nearly matches the known upper bound. Roughly speaking, we show that applying $L_1$-polynomial regression to a smoothed version of the function is essentially best possible. Our techniques involve finding a moment-matching hard distribution by way of linear programming duality. This dual program corresponds exactly to finding a low-degree approximating polynomial to the smoothed version of the target function (which turns out to be the same condition required for the $L_1$-polynomial regression to work). Our explicit SQ lower bound then comes from proving lower bounds on this approximation degree for the class of halfspaces.
toXiv_bot_toot

@metacurity@infosec.exchange
2026-03-20 20:54:23

California city reports ransomware attack as LA transit agency finds ‘unauthorized activity’
therecord.media/california-cit