Replaced article(s) found for math.OC. https://arxiv.org/list/math.OC/new
[1/1]:
- A robust BFGS algorithm for unconstrained nonlinear optimization problems
Yaguang Yang
https://arxiv.org/abs/1212.5929
- Quantum computing and the stable set problem
Alja\v{z} Krpan, Janez Povh, Dunja Pucher
https://arxiv.org/abs/2405.12845 https://mastoxiv.page/@arXiv_mathOC_bot/112483516437815686
- Mean Field Game with Reflected Jump Diffusion Dynamics: A Linear Programming Approach
Zongxia Liang, Xiang Yu, Keyu Zhang
https://arxiv.org/abs/2508.20388 https://mastoxiv.page/@arXiv_mathOC_bot/115111048711698998
- Differential Dynamic Programming for the Optimal Control Problem with an Ellipsoidal Target Set a...
Sungjun Eom, Gyunghoon Park
https://arxiv.org/abs/2509.07546 https://mastoxiv.page/@arXiv_mathOC_bot/115179281556444440
- On the Moreau envelope properties of weakly convex functions
Marien Renaud, Arthur Leclaire, Nicolas Papadakis
https://arxiv.org/abs/2509.13960 https://mastoxiv.page/@arXiv_mathOC_bot/115224514482363803
- Automated algorithm design via Nevanlinna-Pick interpolation
Ibrahim K. Ozaslan, Tryphon T. Georgiou, Mihailo R. Jovanovic
https://arxiv.org/abs/2509.21416 https://mastoxiv.page/@arXiv_mathOC_bot/115286533597711930
- Optimal Control of a Bioeconomic Crop-Energy System with Energy Reinvestment
Othman Cherkaoui Dekkaki
https://arxiv.org/abs/2510.11381 https://mastoxiv.page/@arXiv_mathOC_bot/115372322896073250
- Point Convergence Analysis of the Accelerated Gradient Method for Multiobjective Optimization: Co...
Yingdong Yin
https://arxiv.org/abs/2510.26382 https://mastoxiv.page/@arXiv_mathOC_bot/115468018035252078
- History-Aware Adaptive High-Order Tensor Regularization
Chang He, Bo Jiang, Yuntian Jiang, Chuwen Zhang, Shuzhong Zhang
https://arxiv.org/abs/2511.05788
- Equivalence of entropy solutions and gradient flows for pressureless 1D Euler systems
Jos\'e Antonio Carrillo, Sondre Tesdal Galtung
https://arxiv.org/abs/2312.04932 https://mastoxiv.page/@arXiv_mathAP_bot/111560077272113052
- Kernel Modelling of Fading Memory Systems
Yongkang Huo, Thomas Chaffey, Rodolphe Sepulchre
https://arxiv.org/abs/2403.11945 https://mastoxiv.page/@arXiv_eessSY_bot/112121123836064435
- The Maximum Theoretical Ground Speed of the Wheeled Vehicle
Altay Zhakatayev, Mukatai Nemerebayev
https://arxiv.org/abs/2502.15341 https://mastoxiv.page/@arXiv_physicsclassph_bot/114057765769441123
- Hessian stability and convergence rates for entropic and Sinkhorn potentials via semiconcavity
Giacomo Greco, Luca Tamanini
https://arxiv.org/abs/2504.11133 https://mastoxiv.page/@arXiv_mathPR_bot/114346453424694503
- Optimizing the ground state energy of the three-dimensional magnetic Dirichlet Laplacian with con...
Matthias Baur
https://arxiv.org/abs/2504.21597 https://mastoxiv.page/@arXiv_mathph_bot/114431404740241516
- A localized consensus-based sampling algorithm
Arne Bouillon, Alexander Bodard, Panagiotis Patrinos, Dirk Nuyens, Giovanni Samaey
https://arxiv.org/abs/2505.24861 https://mastoxiv.page/@arXiv_mathNA_bot/114612580684567066
- A Novel Sliced Fused Gromov-Wasserstein Distance
Moritz Piening, Robert Beinert
https://arxiv.org/abs/2508.02364 https://mastoxiv.page/@arXiv_csLG_bot/114976243138728278
- Minimal Regret Walras Equilibria for Combinatorial Markets via Duality, Integrality, and Sensitiv...
Alo\"is Duguet, Tobias Harks, Martin Schmidt, Julian Schwarz
https://arxiv.org/abs/2511.09021 https://mastoxiv.page/@arXiv_csGT_bot/115541243299714775
toXiv_bot_toot
Dette er et problem mange av oss sliter med. Foreldre som er ikke-digitale i en digital verden, og systemene stŸtter ikke stedfortredere med fullmakter til å hjelpe!
https://www.nrk.no/ytring/fra-fullmakt-til-frustrasjon-1.17717776
Sam Altman: ChatGPT macht weniger Gedankenstriche
In einem Post bei X erklärt der OpenAI-Chef, dass man ein leidiges Problem mit den überlangen Querstrichen in den Griff bekommen hat.
https://www.
@…
So to reiterate this conversation:
You: Passkeys don't have problems A, B, C and D!
Me: Actually B is still a problem.
You: Yeah well, B is also a problem for passwords! And so is F and G!
Me: Yes, but B is still a problem.
You: But if I hacked the pentagon, then Z would also be a problem for passwords!
I'm not a…
"LLMs use fewer resources doing $task than humans so using them isn't an ecological problem."
So what are you arguing for? What happens with the humans we no longer "need"?
That argument leads only to monstrosity.
»curl — Projekt beendet Bug-Bounty-Programm:
curl-Maintainer @… hat das Ende des Bug-Bounty-Programms angekündigt. Unbrauchbare KI-Meldungen nahmen wohl überhand.«
Ach was, die KI ist künstlich aber nicht intelligent oder was nun?!?? Ich bin sogar der Meinung, dass dies was die KI angeht noch das rel. kleinste "Problem" ist. Schade dass deswege…
"A new investigation of Elon #Musk’s X by Sky News found that every account set up by reporters, 'no matter their political orientation, was fed a glut of rightwing content', much of which was extreme. The experts it consulted believe this pattern could have resulted only from an algorithm engineered for this purpose, and that 'an algorithmic bias must be decided by senior people at …
Ran into a problem in prod?
Just generate a fake cloudflare error page and blame it on them - gives you time to fix.
#foss
Is #AI really just dumb statistics? "Olympiad-level physics problem-solving presents a significant challenge for both humans and artificial intelligence (AI), as it requires a sophisticated integration of precise calculation, abstract reasoning, and a fundamental grasp of physical principles," says the (abstract of the) paper https://arxiv.org/abs/2511.10515: "The Chinese Physics Olympiad (CPhO), renowned for its complexity and depth, serves as an ideal and rigorous testbed for these advanced capabilities. In this paper, we introduce LOCA-R (LOgical Chain Augmentation for Reasoning), an improved version of the LOCA framework adapted for complex reasoning, and apply it to the CPhO 2025 theory examination. LOCA-R achieves a near-perfect score of 313 out of 320 points, solidly surpassing the highest-scoring human competitor and significantly outperforming all baseline methods." Oops ...?
I don’t know what I would do without @…. He always seems to have the right solution to a problem.
@…
Disagree on one point:
You do need to worry about how the passkey is stored, least you loose access to the credential manager that holds all your passkeys.
I know that’s a problem being worked on, I appreciate everyone involved, but let’s not pretend it’s a non-problem.
@…
RE: https://fediscience.org/@simon_on_energy/115728941757341018
The solution to this problem is very simple: just stop doing peer reviews.
OpenAI says ChatGPT will now ditch em dashes if users tell it to; em dashes have become telltale signs that supposedly signals text written by AI (Sarah Perez/TechCrunch)
https://techcrunch.com/2025/11/14/openai-says-its-fixed-chatgpts-em-dash-problem/
@… It's already a security vulnerability. (CVE-2025-0101) (CVE-2025-1235)(CVE-2025-55068)
And quite expensive for Alstom for example https://y2k38.ch/herstellerhaftung-j…
Over on #Bluesky there was a bit of a controversy over the suspension of Sarah Kendzior. I thought it was an interestingly nontrivial moderation problem, so I wrote up a little case study on how this would have been handled on Mastodon: http…
Katie Porter here.
Trump has no problem creating chaos and pain for Americans until he gets his way.
Democrats need to use our power
– just like we did last week on Election Day
– to send a clear message:
𝗪𝗲 𝘄𝗼𝗻’𝘁 𝘀𝘁𝗮𝗻𝗱 𝗳𝗼𝗿 𝗵𝗶𝗴𝗵𝗲𝗿 𝗰𝗼𝘀𝘁𝘀 𝗮𝗻𝗱 𝗵𝗲𝗮𝗹𝘁𝗵 𝗰𝗮𝗿𝗲 𝗽𝗿𝗲𝗺𝗶𝘂𝗺𝘀 𝘄𝗵𝗶𝗹𝗲 𝗯𝗶𝗹𝗹𝗶𝗼𝗻𝗮𝗶𝗿𝗲𝘀 𝗴𝗲𝘁 𝗲𝘃𝗲𝗻 𝙧𝙞𝙘𝙝𝙚𝙧.
I’ve spent my career protecting people and taking on Wall Street’s corporate greed.
I know what it takes to fight, and to win
– and as California…
Many years ago I was working with a friend to find a bug in a Makefile generator. We had a megabyte or so of Makefile we needed to examine. He was an emacs user. It took him minutes just to open the file. I was using sam. It took about a second for sam to load, and I found the problem before he'd even finished loading the file.
The speed of tools matters, and big files are common nowadays. Things should stay fast as their workload grows. That goes double for interactive tools.
By the way, it still takes me 30 seconds to log in to my bank. I wonder how long it will take when it's an LLM-generated landing page.
https://phanpy.social/#/hachyderm.io/s/115891592999188880
Just keep in mind that the same party also doesn‘t see a problem when school kids die from gun shots. https://mastodon.social/@TwraSun/115547658428106400
After months of not using it, I dusted off my Matrix account thanks to the room created by @… and I encountered a problem due to a loop that prevented me from completing the verification of some devices. Although I solved it, it is certainly not an app suitable for non-techies.
I guess Matrix isn't designed for them, to begin with. However, maybe there…
@… below, is the apparent mismatch between 580.95.x and 580.105.x likely to cause an actual problem?
Or does it simply _look_ a little strange?
Thanks
New packages to be INSTALLED:
drm-66-kmod: 6.6.25.1500068_8 [FreeBSD-ports-kmods]
egl-wayland: 1.1.20 [FreeBSD-ports]
nvidia-driver: 580.95.05 [FreeBSD-port…
Warum die Elektromobilität nur langsam abhebt
Die Stromerzahlen steigen, allerdings langsamer als einst erwartet. Das ist ein Problem für Autokonzerne und EU. Woran es liegt.
https://www.…
I heard from a colleague that a system was just identified with a y2k bug.
Wait, how is that possible?!
A system was using 2 digits to store and transmit the year. To resolve the initial y2k problem, the system employed the date window technique, where that window ended with 2025.
https://en.wikipedia.org/wiki/Da…
The AI market feels like a heist movie, where all participants are in on the initial job, but will start picking each other off as they scramble to make their stake bigger and take out everyone else.
The problem is that in those movies, there's a ton of collateral damage and no one really gets out alive.
If I had a penny for every time I heard something like
"We're going to track increases in productivity that we gain by adopting GenAI"
1. So you're assuming it's an increase
2. Against what control group
3. With no acknowledgement of confounding variables or experiment design
4. Around the...famously open problem of measuring software engineering productivity?
"This project started as a search problem and ended as something more. The most important result isn’t which neighbourhood tops the rankings - it’s the realisation that platforms now quietly structure survival in everyday urban markets. London’s restaurant scene is no longer organised by taste alone. It is organised by visibility that compounds, rent that rises when discovery arrives, and algorithms that allocate attention long before consumers ever show up. What looks like “choice” is increasingly the downstream effect of ranking systems."
How Google Maps quietly allocates survival across London’s restaurants - and how I built a dashboard to see through it
https://laurenleek.substack.com/p/how-google-maps-quietly-allocates
Watch the best Star Wars commentator on YouTube... discuss Kathleen Kennedy. 😁
▶️ Saving Star Wars is simple... but the problem its facing is colossal - Generation Tech
https://youtube.com/watch?v=JWk3YLQHiWc&si=1B-mb6i4BKGSP-uV
Locally Linear Convergence for Nonsmooth Convex Optimization via Coupled Smoothing and Momentum
Reza Rahimi Baghbadorani, Sergio Grammatico, Peyman Mohajerin Esfahani
https://arxiv.org/abs/2511.10239 https://arxiv.org/pdf/2511.10239 https://arxiv.org/html/2511.10239
arXiv:2511.10239v1 Announce Type: new
Abstract: We propose an adaptive accelerated smoothing technique for a nonsmooth convex optimization problem where the smoothing update rule is coupled with the momentum parameter. We also extend the setting to the case where the objective function is the sum of two nonsmooth functions. With regard to convergence rate, we provide the global (optimal) sublinear convergence guarantees of O(1/k), which is known to be provably optimal for the studied class of functions, along with a local linear rate if the nonsmooth term fulfills a so-call locally strong convexity condition. We validate the performance of our algorithm on several problem classes, including regression with the l1-norm (the Lasso problem), sparse semidefinite programming (the MaxCut problem), Nuclear norm minimization with application in model free fault diagnosis, and l_1-regularized model predictive control to showcase the benefits of the coupling. An interesting observation is that although our global convergence result guarantees O(1/k) convergence, we consistently observe a practical transient convergence rate of O(1/k^2), followed by asymptotic linear convergence as anticipated by the theoretical result. This two-phase behavior can also be explained in view of the proposed smoothing rule.
toXiv_bot_toot
Ist es Nostalgie, wenn man der SPD von Brandt und Schmidt nachtrauert – oder schlicht politische Sorge? Ich versuche, meine Erinnerungen, Zweifel und Erwartungen an die Sozialdemokratie zu sortieren. Und erkläre, warum ich glaube, dass ihr Verschwinden ein echtes Problem für unsere Demokratie wäre.
RE: https://mastodon.social/@CentralBylines/115543613034480430
This is the big problem with action on climate change: the people in a position to lose out have huge financial resources, and they're more than willing to use them, even with the si…
Gerechtigkeit beim Verkauf von Konzerttickets (Problem Karten sind in Minuten ausverkauft, erscheinen sofort zum doppelten preis auf ticketblrsen):
Tickets können eine Woche lang gekauft werden, eine Anzahlung von 15 euro wird gezahlt. Nach Ende der Woche erhalten die Käufer ihr ticket gegen Restzahlung. Haben mehr Interessenten ein Ticket gekauft als verfügbar sind, werden alle Käufer darüber informiert, wieviele Tickets verkauft wurden. Wer bis eine Woche vor dem Konzert sein Ticket zurüc…
In 2025, a crack team of moms was sent to prison by a kangaroo court for a crime they didn't commit. These mom’s promptly escaped from a maximum security stockade to the Minneapolis underground. Today, still wanted by the government they survive as wine drinkers of fortune. If you have a problem, if no one else can help, and if you can find them....maybe you can hire The Wine Moms.
#WineMoms
When i use #icecubesapp, my timeline loads max 39 Posts. Regardless how many there are. If i activate full loading, it loads nothing.
Loading local or federated timelines works at night, when less people post.
This way, the app is not usable for me.
I have this problem with no other app.
Paging is no option?
@…
Totally paracompact spaces and the Menger covering property
Davide Giacopello, Maddalena Bonanzinga, Piotr Szewczak
https://arxiv.org/abs/2511.10252 https://arxiv.org/pdf/2511.10252 https://arxiv.org/html/2511.10252
arXiv:2511.10252v1 Announce Type: new
Abstract: A topological space is totally paracompact if any base of this space contains a locally finite subcover. We focus on a problem of Curtis whether in the class of regular Lindel\"of spaces total paracompactness is equivalent to the Menger covering property. To this end we consider topological spaces with certain dense subsets. It follows from our results that the above equivalence holds in the class of Lindel\"of GO-spaces defined on subsets of reals. We also provide a game-theoretical proof that any regular Menger space is totally paracompact and show that in the class of first-countable spaces the Menger game and a partial open neighborhood assignment game of Aurichi are equivalent. We also show that if $\mathfrak{b}=\omega_1$, then there is an uncountable subspace of the Sorgenfrey line whose all finite powers are Lindel\"of, which is a strengthening of a famous result due to Michael.
toXiv_bot_toot
Die Bundeswehr befindet sich im digitalen Aufrüstungsmodus und sucht händeringend nach IT-Fachkräften! 💻 Mit 139.500 Bewerbungen im letzten Jahr verzeichnet sie zwar ein beeindruckendes Plus von einem Drittel gegenüber dem Vorjahr, doch besonders im IT-Bereich bleibt die Personalgewinnung schwierig.
Zum Artikel: …
Why Your Problem-Solving Approach Keeps Failing (Complicated vs Complex)
https://www.youtube.com/watch?v=w3Keu9Gcl0g
Verification of Sequential Convex Programming for Parametric Non-convex Optimization
Rajiv Sambharya, Nikolai Matni, George Pappas
https://arxiv.org/abs/2511.10622 https://arxiv.org/pdf/2511.10622 https://arxiv.org/html/2511.10622
arXiv:2511.10622v1 Announce Type: new
Abstract: We introduce a verification framework to exactly verify the worst-case performance of sequential convex programming (SCP) algorithms for parametric non-convex optimization. The verification problem is formulated as an optimization problem that maximizes a performance metric (e.g., the suboptimality after a given number of iterations) over parameters constrained to be in a parameter set and iterate sequences consistent with the SCP update rules. Our framework is general, extending the notion of SCP to include both conventional variants such as trust-region, convex-concave, and prox-linear methods, and algorithms that combine convex subproblems with rounding steps, as in relaxing and rounding schemes. Unlike existing analyses that may only provide local guarantees under limited conditions, our framework delivers global worst-case guarantees--quantifying how well an SCP algorithm performs across all problem instances in the specified family. Applications in control, signal processing, and operations research demonstrate that our framework provides, for the first time, global worst-case guarantees for SCP algorithms in the parametric setting.
toXiv_bot_toot
@…
Das ist sehr interessant. In welchem Embedded SW Umfeld bist du unterwegs? Seit wann würdest du sagen haben die Leute in deinem Umfeld das Problem im Griff?
@…
"I have little to no sympathy for Tim Davie. He has helped create the problem by constantly opining on the BBC being too liberal. He has legitimised the critique which has toppled him. He appeased the same forces who have brought him down"
The truth about impartiality at the BBC - by Lewis Goodall
https://
@… hab ein komisches Problem - wollte mich zur Vorbereitung auf #39c3 im Guru3 einloggen, aber es hiess "Please enter a correct username and password." OK, Passwort zurückgesetzt per Mail, neues Passwort gesetzt - gleiches Problem.
Ist was mit meinem Acco…
RE: https://mastodon.green/@gerrymcgovern/115541855912936152
Education towards responsible behaviour is always good, but trying to solve a problem by changing something other than what caused it is deflection.
(And kids should be lead to become …
Crypto casinos have become online gambling havens for teens and problem gamblers, propped up by operators who turn social media influencers into recruiters (New York Times)
https://www.nytimes.com/interactive/2025/1
Gmail-Störung: Exchange ActiveSync funktioniert wieder
Die E-Mail-Verarbeitung von Exchange-Mailern in Gmail war wochenlang gestört. Das Problem hat Google ohne weitere Hinweise gelöst.
https://www.
Web dependencies are broken. Can we fix them?
Dear JS ecosystem, I love you, but you have a dependency management problem when it comes to the Web, and the time has come for an intervention.
— by @…
🤷 https://
It appears that the latest version of Portainer has a significant bug that prevents access to the local server environment, meaning you cannot manage your containers.
Until the developers fix the problem, the temporary solution is to use version 2.20.2.
https://github.com/portainer/portainer
Indonesia and Malaysia block #Grok access
UK threatens ban as explicit deepfake problem grows
Elon Musk has called the government intervention
an attack on free speech
https://mashable.com/article/grok-bloc<…
Benders Decomposition for Passenger-Oriented Train Timetabling with Hybrid Periodicity
Zhiyuan Yao, Anita Sch\"obel, Lei Nie, Sven J\"ager
https://arxiv.org/abs/2511.09892 https://arxiv.org/pdf/2511.09892 https://arxiv.org/html/2511.09892
arXiv:2511.09892v1 Announce Type: new
Abstract: Periodic timetables are widely adopted in passenger railway operations due to their regular service patterns and well-coordinated train connections. However, fluctuations in passenger demand require varying train services across different periods, necessitating adjustments to the periodic timetable. This study addresses a hybrid periodic train timetabling problem, which enhances the flexibility and demand responsiveness of a given periodic timetable through schedule adjustments and aperiodic train insertions, taking into account the rolling stock circulation. Since timetable modifications may affect initial passenger routes, passenger routing is incorporated into the problem to guide planning decisions towards a passenger-oriented objective. Using a time-space network representation, the problem is formulated as a dynamic railway service network design model with resource constraints. To handle the complexity of real-world instances, we propose a decomposition-based algorithm integrating Benders decomposition and column generation, enhanced with multiple preprocessing and accelerating techniques. Numerical experiments demonstrate the effectiveness of the algorithm and highlight the advantage of hybrid periodic timetables in reducing passenger travel costs.
toXiv_bot_toot
@… @… I agree, and haven’t ever actually done something like that myself. But the problem is, you know there are people out there who don’t hold themselves to the same moral standard.
Digitale Aufrüstung: Die Bundeswehr sucht IT-Experten
Die Truppenstärke der Bundeswehr soll stark steigen – durch den neuen Wehrdienst sowie Berufs- und Zeitsoldaten mit speziellem Fachwissen, etwa in der IT.
https://…
An inexact semismooth Newton-Krylov method for semilinear elliptic optimal control problem
Shiqi Chen, Xuesong Chen
https://arxiv.org/abs/2511.10058 https://arxiv.org/pdf/2511.10058 https://arxiv.org/html/2511.10058
arXiv:2511.10058v1 Announce Type: new
Abstract: An inexact semismooth Newton method has been proposed for solving semi-linear elliptic optimal control problems in this paper. This method incorporates the generalized minimal residual (GMRES) method, a type of Krylov subspace method, to solve the Newton equations and utilizes nonmonotonic line search to adjust the iteration step size. The original problem is reformulated into a nonlinear equation through variational inequality principles and discretized using a second-order finite difference scheme. By leveraging slanting differentiability, the algorithm constructs semismooth Newton directions and employs GMRES method to inexactly solve the Newton equations, significantly reducing computational overhead. A dynamic nonmonotonic line search strategy is introduced to adjust stepsizes adaptively, ensuring global convergence while overcoming local stagnation. Theoretical analysis demonstrates that the algorithm achieves superlinear convergence near optimal solutions when the residual control parameter $\eta_k$ approaches to 0. Numerical experiments validate the method's accuracy and efficiency in solving semilinear elliptic optimal control problems, corroborating theoretical insights.
toXiv_bot_toot
Trump: Netflix-Stärke könnte Problem bei Warner-Deal sein
Donald Trump will persönlich an der Entscheidung der US-Regierung zur Übernahme von Warner Brothers durch Netflix beteiligt sein.
https://www.
Global Convergence of Four-Layer Matrix Factorization under Random Initialization
Minrui Luo, Weihang Xu, Xiang Gao, Maryam Fazel, Simon Shaolei Du
https://arxiv.org/abs/2511.09925 https://arxiv.org/pdf/2511.09925 https://arxiv.org/html/2511.09925
arXiv:2511.09925v1 Announce Type: new
Abstract: Gradient descent dynamics on the deep matrix factorization problem is extensively studied as a simplified theoretical model for deep neural networks. Although the convergence theory for two-layer matrix factorization is well-established, no global convergence guarantee for general deep matrix factorization under random initialization has been established to date. To address this gap, we provide a polynomial-time global convergence guarantee for randomly initialized gradient descent on four-layer matrix factorization, given certain conditions on the target matrix and a standard balanced regularization term. Our analysis employs new techniques to show saddle-avoidance properties of gradient decent dynamics, and extends previous theories to characterize the change in eigenvalues of layer weights.
toXiv_bot_toot
Measuring dissimilarity between convex cones by means of max-min angles
Welington de Oliveira, Valentina Sessa, David Sossa
https://arxiv.org/abs/2511.10483 https://arxiv.org/pdf/2511.10483 https://arxiv.org/html/2511.10483
arXiv:2511.10483v1 Announce Type: new
Abstract: This work introduces a novel dissimilarity measure between two convex cones, based on the max-min angle between them. We demonstrate that this measure is closely related to the Pompeiu-Hausdorff distance, a well-established metric for comparing compact sets. Furthermore, we examine cone configurations where the measure admits simplified or analytic forms. For the specific case of polyhedral cones, a nonconvex cutting-plane method is deployed to compute, at least approximately, the measure between them. Our approach builds on a tailored version of Kelley's cutting-plane algorithm, which involves solving a challenging master program per iteration. When this master program is solved locally, our method yields an angle that satisfies certain necessary optimality conditions of the underlying nonconvex optimization problem yielding the dissimilarity measure between the cones. As an application of the proposed mathematical and algorithmic framework, we address the image-set classification task under limited data conditions, a task that falls within the scope of the \emph{Few-Shot Learning} paradigm. In this context, image sets belonging to the same class are modeled as polyhedral cones, and our dissimilarity measure proves useful for understanding whether two image sets belong to the same class.
toXiv_bot_toot
YouTube geht wieder gegen Adblocker vor
In den USA häuften sich die Ausfallmeldungen für die Seite. Dabei war das Problem ein ganz anderes.
https://www.heise.de/news/YouTube-geht-wie
Global Solutions to Non-Convex Functional Constrained Problems with Hidden Convexity
Ilyas Fatkhullin, Niao He, Guanghui Lan, Florian Wolf
https://arxiv.org/abs/2511.10626 https://arxiv.org/pdf/2511.10626 https://arxiv.org/html/2511.10626
arXiv:2511.10626v1 Announce Type: new
Abstract: Constrained non-convex optimization is fundamentally challenging, as global solutions are generally intractable and constraint qualifications may not hold. However, in many applications, including safe policy optimization in control and reinforcement learning, such problems possess hidden convexity, meaning they can be reformulated as convex programs via a nonlinear invertible transformation. Typically such transformations are implicit or unknown, making the direct link with the convex program impossible. On the other hand, (sub-)gradients with respect to the original variables are often accessible or can be easily estimated, which motivates algorithms that operate directly in the original (non-convex) problem space using standard (sub-)gradient oracles. In this work, we develop the first algorithms to provably solve such non-convex problems to global minima. First, using a modified inexact proximal point method, we establish global last-iterate convergence guarantees with $\widetilde{\mathcal{O}}(\varepsilon^{-3})$ oracle complexity in non-smooth setting. For smooth problems, we propose a new bundle-level type method based on linearly constrained quadratic subproblems, improving the oracle complexity to $\widetilde{\mathcal{O}}(\varepsilon^{-1})$. Surprisingly, despite non-convexity, our methodology does not require any constraint qualifications, can handle hidden convex equality constraints, and achieves complexities matching those for solving unconstrained hidden convex optimization.
toXiv_bot_toot
S-D-RSM: Stochastic Distributed Regularized Splitting Method for Large-Scale Convex Optimization Problems
Maoran Wang, Xingju Cai, Yongxin Chen
https://arxiv.org/abs/2511.10133 https://arxiv.org/pdf/2511.10133 https://arxiv.org/html/2511.10133
arXiv:2511.10133v1 Announce Type: new
Abstract: This paper investigates the problems large-scale distributed composite convex optimization, with motivations from a broad range of applications, including multi-agent systems, federated learning, smart grids, wireless sensor networks, compressed sensing, and so on. Stochastic gradient descent (SGD) and its variants are commonly employed to solve such problems. However, existing algorithms often rely on vanishing step sizes, strong convexity assumptions, or entail substantial computational overhead to ensure convergence or obtain favorable complexity. To bridge the gap between theory and practice, we integrate consensus optimization and operator splitting techniques (see Problem Reformulation) to develop a novel stochastic splitting algorithm, termed the \emph{stochastic distributed regularized splitting method} (S-D-RSM). In practice, S-D-RSM performs parallel updates of proximal mappings and gradient information for only a randomly selected subset of agents at each iteration. By introducing regularization terms, it effectively mitigates consensus discrepancies among distributed nodes. In contrast to conventional stochastic methods, our theoretical analysis establishes that S-D-RSM achieves global convergence without requiring diminishing step sizes or strong convexity assumptions. Furthermore, it achieves an iteration complexity of $\mathcal{O}(1/\epsilon)$ with respect to both the objective function value and the consensus error. Numerical experiments show that S-D-RSM achieves up to 2--3$\times$ speedup compared to state-of-the-art baselines, while maintaining comparable or better accuracy. These results not only validate the algorithm's theoretical guarantees but also demonstrate its effectiveness in practical tasks such as compressed sensing and empirical risk minimization.
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Convergence analysis of inexact MBA method for constrained upper-$\mathcal{C}^2$ optimization problems
Ruyu Liu, Shaohua Pan
https://arxiv.org/abs/2511.09940 https://arxiv.org/pdf/2511.09940 https://arxiv.org/html/2511.09940
arXiv:2511.09940v1 Announce Type: new
Abstract: This paper concerns a class of constrained optimization problems in which, the objective and constraint functions are both upper-$\mathcal{C}^2$. For such nonconvex and nonsmooth optimization problems, we develop an inexact moving balls approximation (MBA) method by a workable inexactness criterion for the solving of subproblems. By leveraging a global error bound for the strongly convex program associated with parametric optimization problems, we establish the full convergence of the iterate sequence under the partial bounded multiplier property (BMP) and the Kurdyka-{\L}ojasiewicz (KL) property of the constructed potential function, and achieve the local convergence rate of the iterate and objective value sequences if the potential function satisfies the KL property of exponent $q\in[1/2,1)$. A verifiable condition is also provided to check whether the potential function satisfies the KL property of exponent $q\in[1/2,1)$ at the given critical point. To the best of our knowledge, this is the first implementable inexact MBA method with a full convergence certificate for the constrained nonconvex and nonsmooth optimization problem.
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