Tootfinder

Just finished "I'm Awful, Thanks" by Lara Pickle. A good story that serves as a guide to managing emotions, although it's actually a cute story too, not just framing for the mental health discussion.
That said, I feel like it doesn't get far enough into the details of accepting self-control as our only form of real control vs. understanding that some events outside our control aren't fair or are others' attacks, and trying to manage our own emotions as our only response is a disservice to ourselves and others. Even further, I suspect that the HR resolution depicted here, while not impossible, is less frequent than much worse outcomes, which is part of a larger pattern of systemic assaults on our mental health that aren't totally solvable with individual emotional regulation.
Sure, leveling up one's control of ones own emotions and learning to accept and manage a range of emotions is super useful and it's a good thing overall, but the systemic problems of late stage capitalism are real, and making it seem like everyone is responsible for managing their own mental health in the face of these problems helps avoid confronting them.
Still, it's a good book overall, with vibrant art and a well-structured plot.
#AmReading #ReadingNow

mild panic that the boiler didn’t turn on when i asked it for more hot water when the tap was running cold earlier
i left it to deal with after i had finished cooking
but it did turn on at the scheduled central heating time
hmm
i wonder if that is a misconfiguration or something more serious
(i have doubts about the noises from one of the valve actuators)

Ich finde, wir sollten nicht immer so schlecht über Microsoft reden. Ich bin zum Beispiel mit meinem Xbox Elite Wireless Controller Series 2 sehr zufrieden. Also, unter Linux funktioniert der hervorragend.

Italian Prime Minister Giorgia Meloni remains confident, despite legal setbacks,
that the deportation facilities in Albania, promoted by her right-wing government, will function as planned.
Meloni pointed to an agreement within the EU on a tougher stance on migration.
The EU states recently agreed in Brussels to increase pressure on rejected asylum seekers and deport them more efficiently.
Return centres in countries outside the EU should also be possible in the future…

Meloni says Italian deportation camps in Albania will work - EUROPE SAYS
Italian Prime Minister Giorgia Meloni remains confident, despite legal setbacks, that the deportation facilities in Albania, promoted by her right-wing

Crosslisted article(s) found for math.OC. https://arxiv.org/list/math.OC/new
[1/1]:
- Optimal control of Volterra integral diffusions and application to contract theory
Dylan Possama\"i, Mehdi Talbi
https://arxiv.org/abs/2511.09701 https://mastoxiv.page/@arXiv_mathPR_bot/115547093766733637
- Generalized infinite dimensional Alpha-Procrustes based geometries
Salvish Goomanee, Andi Han, Pratik Jawanpuria, Bamdev Mishra
https://arxiv.org/abs/2511.09801 https://mastoxiv.page/@arXiv_statML_bot/115547135711272091
- Sample Complexity of Quadratically Regularized Optimal Transport
Alberto Gonz\'alez-Sanz, Eustasio del Barrio, Marcel Nutz
https://arxiv.org/abs/2511.09807 https://mastoxiv.page/@arXiv_mathST_bot/115546975796760368
- On the Convergence of Overparameterized Problems: Inherent Properties of the Compositional Struct...
Arthur Castello Branco de Oliveira, Dhruv Jatkar, Eduardo Sontag
https://arxiv.org/abs/2511.09810 https://mastoxiv.page/@arXiv_csLG_bot/115547543989283588
- Implicit Multiple Tensor Decomposition
Kunjing Yang, Libin Zheng, Minru Bai
https://arxiv.org/abs/2511.09916 https://mastoxiv.page/@arXiv_mathNA_bot/115547169767663335
- Theoretical Analysis of Resource-Induced Phase Transitions in Estimation Strategies
Takehiro Tottori, Tetsuya J. Kobayashi
https://arxiv.org/abs/2511.10184 https://mastoxiv.page/@arXiv_physicsbioph_bot/115546979073652600
- Zeroes and Extrema of Functions via Random Measures
Athanasios Christou Micheas
https://arxiv.org/abs/2511.10293 https://mastoxiv.page/@arXiv_statME_bot/115547493525198835
- Operator Models for Continuous-Time Offline Reinforcement Learning
Nicolas Hoischen, Petar Bevanda, Max Beier, Stefan Sosnowski, Boris Houska, Sandra Hirche
https://arxiv.org/abs/2511.10383 https://mastoxiv.page/@arXiv_statML_bot/115547254989932993
- On topological properties of closed attractors
Wouter Jongeneel
https://arxiv.org/abs/2511.10429 https://mastoxiv.page/@arXiv_mathDS_bot/115547276594491411
- Learning parameter-dependent shear viscosity from data, with application to sea and land ice
Gonzalo G. de Diego, Georg Stadler
https://arxiv.org/abs/2511.10452 https://mastoxiv.page/@arXiv_mathNA_bot/115547323782478749
- Formal Verification of Control Lyapunov-Barrier Functions for Safe Stabilization with Bounded Con...
Jun Liu
https://arxiv.org/abs/2511.10510 https://mastoxiv.page/@arXiv_eessSY_bot/115547429321496393
- Direction-of-Arrival and Noise Covariance Matrix joint estimation for beamforming
Vitor Gelsleichter Probst Curtarelli
https://arxiv.org/abs/2511.10639 https://mastoxiv.page/@arXiv_eessAS_bot/115547188796143762
toXiv_bot_toot

Ah! «Le Gouvernement a décidé de retirer le décret sur la contribution de crise de 0,7 % sur les salaires de la fonction publique (-24 millions).»
https://tooting.ch/@etatdevaud/115707561491415218

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

It’s been 36 years since a mass femicide occurred at École Polytechnique in Montréal.
A man shot and killed 14 women because of their sex.
Described as “violent misogyny” by the federal government,
the killings have nonetheless never officially been called femicide in Canada
despite its global recognition as one of the most vivid examples of femicide in the western world.
Women and girls continue to be killed every two days somewhere in Canada, mostly by men. …

Too True Crime
True Crime Podcast · Since 2020, there have been at least 580 women and girls killed by men in acts of gender-related violence across the country. This is called femicide. Too True Crime is a podcast series designed to sh…

Riccati-ZORO: An efficient algorithm for heuristic online optimization of internal feedback laws in robust and stochastic model predictive control
Florian Messerer, Yunfan Gao, Jonathan Frey, Moritz Diehl
https://arxiv.org/abs/2511.10473 https://arxiv.org/pdf/2511.10473 https://arxiv.org/html/2511.10473
arXiv:2511.10473v1 Announce Type: new
Abstract: We present Riccati-ZORO, an algorithm for tube-based optimal control problems (OCP). Tube OCPs predict a tube of trajectories in order to capture predictive uncertainty. The tube induces a constraint tightening via additional backoff terms. This backoff can significantly affect the performance, and thus implicitly defines a cost of uncertainty. Optimizing the feedback law used to predict the tube can significantly reduce the backoffs, but its online computation is challenging.
Riccati-ZORO jointly optimizes the nominal trajectory and uncertainty tube based on a heuristic uncertainty cost design. The algorithm alternates between two subproblems: (i) a nominal OCP with fixed backoffs, (ii) an unconstrained tube OCP, which optimizes the feedback gains for a fixed nominal trajectory. For the tube optimization, we propose a cost function informed by the proximity of the nominal trajectory to constraints, prioritizing reduction of the corresponding backoffs. These ideas are developed in detail for ellipsoidal tubes under linear state feedback. In this case, the decomposition into the two subproblems yields a substantial reduction of the computational complexity with respect to the state dimension from $\mathcal{O}(n_x^6)$ to $\mathcal{O}(n_x^3)$, i.e., the complexity of a nominal OCP.
We investigate the algorithm in numerical experiments, and provide two open-source implementations: a prototyping version in CasADi and a high-performance implementation integrated into the acados OCP solver.
toXiv_bot_toot