🇺🇦 #NowPlaying on KEXP's #VarietyMix
Kassa Overall:
🎵 BIG POPPA
#KassaOverall
https://kassaoverall.bandcamp.com/track/big-poppa
https://open.spotify.com/track/40KpjmBOEjtnhx5vLX8NJi
One of the interesting articles that came after #KubeCon is touching the problem of the platform engineering anti-patterns. Is there anything in particular that bothers you and you want to discuss it at #DevOpsDays #Prague
Ukraine evakuiert Dörfer nahe Kupjansk
Die ukrainischen Behörden haben die Evakuierung zahlreicher Dörfer in der Nähe der fast vollständig zerstörten nordöstlichen Stadt Kupjansk angeordnet. Als Grund wurde die "sich verschlechternde Sicherheitslage" in der Region genannt, die schweren russischen Angriffen ausgesetzt ist.
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Unclear to me why no one ever mentions Strongbox in #PasswordManager reviews. It is a perfectly fine PM for macOS/iOS/iPadOS that has a rich set of sync options, most of which don't involve any 2nd/3rd party storage. It stores its databases in KeePass2.x (kdbx v4) format, so it is data-compatible with the many variations of KeePass.
(I use it with SSH/SCP sync, so as long as I’m at…
Ukraine evakuiert Dörfer nahe Kupjansk
Die ukrainischen Behörden haben die Evakuierung zahlreicher Dörfer in der Nähe der fast vollständig zerstörten nordöstlichen Stadt Kupjansk angeordnet. Als Grund wurde die "sich verschlechternde Sicherheitslage" in der Region genannt, die schweren russischen Angriffen ausgesetzt ist.
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Minimizing smooth Kurdyka-{\L}ojasiewicz functions via generalized descent methods: Convergence rate and complexity
Masoud Ahookhosh, Susan Ghaderi, Alireza Kabgani, Morteza Rahimi
https://arxiv.org/abs/2511.10414 https://arxiv.org/pdf/2511.10414 https://arxiv.org/html/2511.10414
arXiv:2511.10414v1 Announce Type: new
Abstract: This paper addresses the generalized descent algorithm (DEAL) for minimizing smooth functions, which is analyzed under the Kurdyka-{\L}ojasiewicz (KL) inequality. In particular, the suggested algorithm guarantees a sufficient decrease by adapting to the cost function's geometry. We leverage the KL property to establish the global convergence, convergence rates, and complexity. A particular focus is placed on the linear convergence of generalized descent methods. We show that the constant step-size and Armijo line search strategies along a generalized descent direction satisfy our generalized descent condition. Additionally, for nonsmooth functions by leveraging the smoothing techniques such as forward-backward and high-order Moreau envelopes, we show that the boosted proximal gradient method (BPGA) and the boosted high-order proximal-point (BPPA) methods are also specific cases of DEAL, respectively. It is notable that if the order of the high-order proximal term is chosen in a certain way (depending on the KL exponent), then the sequence generated by BPPA converges linearly for an arbitrary KL exponent. Our preliminary numerical experiments on inverse problems and LASSO demonstrate the efficiency of the proposed methods, validating our theoretical findings.
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🇺🇦 #NowPlaying on #KEXP's #Early
Kassa Overall:
🎵 BIG POPPA
#KassaOverall
https://kassaoverall.bandcamp.com/track/big-poppa
https://open.spotify.com/track/40KpjmBOEjtnhx5vLX8NJi