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@arXiv_mathOC_bot@mastoxiv.page
2025-06-16 08:38:19

Complexity of normalized stochastic first-order methods with momentum under heavy-tailed noise
Chuan He, Zhaosong Lu, Defeng Sun, Zhanwang Deng
https://arxiv.org/abs/2506.11214

Complexity of normalized stochastic first-order methods with momentum under heavy-tailed noise
In this paper, we propose practical normalized stochastic first-order methods with Polyak momentum, multi-extrapolated momentum, and recursive momentum for solving unconstrained optimization problems. These methods employ dynamically updated algorithmic parameters and do not require explicit knowledge of problem-dependent quantities such as the Lipschitz constant or noise bound. We establish first-order oracle complexity results for finding approximate stochastic stationary points under heavy-t…

@x_tof@verkehrswende.social
2025-06-16 23:07:35

ich habe ein Packster Lastenrad.
Bei dem musste 2020 nach etwa drei Jahren die Federgabel getauscht werden (in einer Fachwerkstatt). Die neue Gabel hatte dann eine Steckachse, also musste auch noch ein neues Vorderrad her.
Seitdem hatte ich beim Fahren damit immer ein schlechtes Gefühl!
Vorgestern ist mir aufgefallen, dass die Speichen zwar gekreuzt, aber nicht "übereinander" sind, alle, konsequent. Von einer Radwerkstatt so durchgeführt.

@berlinbuzzwords@floss.social
2025-06-16 06:30:05

For all online participants, find your Venueless access link in your order confirmation email or our email from June 13.
Our platform is user-friendly; navigate through the left menu bar for live streams of all four stages. There's a chat for comments and interaction next to the video streams, and you can switch to the Q&A function above the chat for questions to be read to the speakers. Have questions? Our Online Stage Hosts are here to help.
Thanks for joining us online…

A laptop screen on which a bbuzz session is streamed

@arXiv_mathOC_bot@mastoxiv.page
2025-06-16 09:31:29

High Probability Convergence of Distributed Clipped Stochastic Gradient Descent with Heavy-tailed Noise
Yuchen Yang, Kaihong Lu, Long Wang
https://arxiv.org/abs/2506.11647

High Probability Convergence of Distributed Clipped Stochastic Gradient Descent with Heavy-tailed Noise
In this paper, the problem of distributed optimization is studied via a network of agents. Each agent only has access to a noisy gradient of its own objective function, and can communicate with its neighbors via a network. To handle this problem, a distributed clipped stochastic gradient descent algorithm is proposed, and the high probability convergence of the algorithm is studied. Existing works on distributed algorithms involving stochastic gradients only consider the light-tailed noises. Di…

@kazys@mastodon.social
2025-04-12 00:50:29

A preview of Monday’s post in case you need a distraction from the state of the world.
https://varnelis.net/works_and_projects/the-generative-turn-on-ais-as-stochastic-parrots-and-art/

The Generative Turn: On AIs as Stochastic Parrots and Art - varnelis.net
Kazys Varnelis, Stochastic Parrots, 2025.Large Language Model (LLM)-based Artificial Intelligences have been derided for hallucinating—a topic that I addressed in my last essay, “The New Surrealism. On AI and Hallucinations,”—and labeled “stochastic parrots,” supposedly incapable of generating authentic meaning beyond remixed texts. Coined by researcher Emily Bender and her colleagues, the term “stochastic parrots” describes ...

@seedling@dice.camp
2025-06-07 06:14:05

I had this idea for a Cairn lifepath generator where there are three stages of life and you roll 1d6 for your stats at each stage, and also get appropriate items.
It has not been playtested, it's barely been proofread, but I've been having a lot of fun generating guys
perchance.org/lt8m69fg35
#ttrpg #CairnRpg

Based on Cairn.

You have 2 HP.

Your childhood: You grew up in relative luxury, the child of minor nobility. You have a gold holy symbol on a cord (petty).
Add 2 to STR, 3 to DEX, 5 to WIL, and an extra 2 gp.

After, you were trained in matters of religion.
Add 3 to STR, 2 to DEX, 6 to WIL.
Start with a staff ( d6) and a holy symbol which the undead avoid.

You never became a priest because you were accused of heresy
Add 2 to STR, 5 to DEX, 5 to WIL
You might know facts about cults you encount…

You have 5 HP.

Your childhood: You were orphaned (or so they believe). You were found with a religious amulet (petty). Add 2 to STR, 4 to DEX and 4 to DEX.

As you grew up, you you started working in the mines.
Add 5 to STR, 5 to DEX, 3 to WIL
Start with a pickaxe ( d8) and helmet (1 ).

After several years, after a friend died in a cave-in, you knew you had to leave that life behind.
You have a cart and a strong but stubborn donkey.
Add 1 to STR, 2 to DEX, 5 to WIL.

You have 6 HP.

Your childhood: You grew up doing hard but honest work in the fields. You have a roughly carved wooden religious amulet (petty).
Add 3 to STR, 5 to DEX, 5 to WIL.

As you grew older, you learned from the village herbalist.
Add 3 to STR, 3 to DEX, 4 to WIL.
Start with a poisoned sickle ( d6, target is impaired if blood is drawn), 3 uses of a medicine restoring d4 STR, and knowledge of the effects of common herbs.

You left town after you traveled too deep in the woods and found y…

@arXiv_mathOC_bot@mastoxiv.page
2025-06-16 09:51:10

Convergence of Momentum-Based Optimization Algorithms with Time-Varying Parameters
Mathukumalli Vidyasagar
https://arxiv.org/abs/2506.11904 https://…

Convergence of Momentum-Based Optimization Algorithms with Time-Varying Parameters
In this paper, we present a unified algorithm for stochastic optimization that makes use of a "momentum" term; in other words, the stochastic gradient depends not only on the current true gradient of the objective function, but also on the true gradient at the previous iteration. Our formulation includes the Stochastic Heavy Ball (SHB) and the Stochastic Nesterov Accelerated Gradient (SNAG) algorithms as special cases. In addition, in our formulation, the momentum term is allowed to vary as a f…

@arXiv_astrophGA_bot@mastoxiv.page
2025-06-16 09:52:39

Unveiling a Population of Strong Galaxy-Galaxy Lensed Faint Dusty Star-Forming Galaxies
Ting-Kai Yang, Chian-Chou Chen, Zhen-Kai Gao, Bovornpratch Vijarnwannaluk, Adarsh Ranjan, Wei-Hao Wang, Caitlin M. Casey, Tomotsugu Goto, Jeyhan S. Kartaltepe, Chayan Mondal, James Pearson, Chris Sedgwick, Stephen Serjeant
https://arxiv.org/a…

Unveiling a Population of Strong Galaxy-Galaxy Lensed Faint Dusty Star-Forming Galaxies
The measurements of the number density of galaxy-galaxy strong lenses can be used to put statistical constraints on the foreground mass distributions. Dusty galaxies uncovered in submillimeter surveys are particularly useful in this regard because of the large volume probed by these surveys. Previous discoveries of strong galaxy-galaxy lensed dusty galaxies are predominantly the brightest in the sky discovered by Herschel, SPT, and Planck. However, models have also predicted a non-negligible fr…

@arXiv_physicsfludyn_bot@mastoxiv.page
2025-06-16 09:27:20

A fast mesh-free boundary integral method for two-phase flow with soluble surfactant
Samantha G. Evans, Michael Siegel, Johannes Tausch, Michael R. Booty
https://arxiv.org/abs/2506.11282

A fast mesh-free boundary integral method for two-phase flow with soluble surfactant
We present an accurate and efficient boundary integral (BI) method for simulating the deformation of drops and bubbles in Stokes flow with soluble surfactant. Soluble surfactant advects and diffuses in bulk fluids while adsorbing and desorbing at interfaces. Since the fluid velocity is coupled to the surfactant concentration, the advection-diffusion equation governing the bulk surfactant concentration $C$ is nonlinear, precluding the Green's function formulation necessary for a BI method. Howev…

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