Tootfinder

This https://arxiv.org/abs/2502.20466 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csGT_…

Semicoarse Correlated Equilibria and LP-Based Guarantees for Gradient Dynamics in Normal-Form Games
Projected gradient ascent is known to satisfy no-external regret as a learning algorithm. However, recent empirical work shows that projected gradient ascent often finds the Nash equilibrium in settings beyond two-player zero-sum interactions or potential games, including those where the set of coarse correlated equilibria is very large. We show that gradient ascent in fact satisfies a stronger class of linear $Φ$-regret in normal-form games; resulting in a refined solution concept which we du…

Rupert Murdoch, the 94-year-old media baron whose fortunes have risen in tandem with Trump’s political ascent,
has turned into an unlikely foe.
Trump has bristled over a Wall Street Journal report that he allegedly sent a suggestive letter to sex offender Jeffrey Epstein for his 50th birthday in 2003.
Trump denied sending the message, calling it a “fake,”
and last month he filed a $10-billion defamation suit against Journal publisher Dow Jones & Co., Murdoch and …

Rupert Murdoch and Donald Trump: Inside their tangled relationship
Trump sued Rupert Murdoch and his News Corp. for $10 billion over the Wall Street Journal's report that Trump allegedly sent a sexually suggestive letter to Jeffrey Epstein for his 50th birthday decades ago.

First day without rain.
Right after work we brought our car to some maintenance and drove back by bike. Well not the direct way, but a fun way 😊
It felt really good!
#cycling #BikeTooter #getoutside

Numerical analysis for computing multiple solutions of semilinear elliptic problems by high-index saddle dynamics: Part I--Index-1 case
Lei Zhang, Xiangcheng Zheng, Shangqin Zhu
https://arxiv.org/abs/2508.01534

Numerical analysis for computing multiple solutions of semilinear elliptic problems by high-index saddle dynamics: Part I--Index-1 case
This work presents a numerical analysis of computing transition states of semilinear elliptic partial differential equations (PDEs) via the high-index saddle dynamics at the index-1 case, or equivalently, the gentlest ascent dynamics. To establish clear connections between saddle dynamics and numerical methods of PDEs, as well as improving their compatibility, we first propose the continuous-in-space formulation of saddle dynamics for semilinear elliptic problems. This formulation yields a para…

Next launch attempt for #Crew11 underway: https://www.youtube.com/watch?v=k0ILMhbWHNQ. "Weather forecast is 60% favorable for liftoff, while teams are keeping an eye on weather along the ascent corridor": https://x.com/SpaceX/status/1951240848470872403

Ascent and descent of Artinian module structures under flat base changes
Tran Do Minh Chau, Le Thanh Nhan
https://arxiv.org/abs/2507.19019 https://arxiv.or…

Ascent and descent of Artinian module structures under flat base changes
Let $φ: R\rightarrow S$ be a flat local homomorphism between commutative Noetherian local rings. In this paper, the ascent and descent of Artinian module structures between $R$ and $S$ are investigated. For an Artinian $R$-module $A$, the structure of $A\otimes_RS$ is described. As an application, the Artinianess of certain local cohomology modules is clarified.

On gradient descent-ascent flows in metric spaces
Noboru Isobe, Sho Shimoyama
https://arxiv.org/abs/2506.20258 https://arxiv.org/pdf/…

On gradient descent-ascent flows in metric spaces
Gradient descent-ascent (GDA) flows play a central role in finding saddle points of bivariate functionals, with applications in optimization, game theory, and robust control. While they are well-understood in Hilbert and Banach spaces via maximal monotone operator theory, their extension to general metric spaces, particularly Wasserstein spaces, has remained largely unexplored. In this paper, we develop a mathematical theory of GDA flows on the product of two complete metric spaces, formulating…

Replaced article(s) found for math.RA. https://arxiv.org/list/math.RA/new
[1/1]:
- Ascent and descent of Gorenstein homological properties
Jian Liu, Wei Ren

Non-Euclidean dual gradient ascent for entropically regularized linear and semidefinite programming
Yuhang Cai, Michael Lindsey
https://arxiv.org/abs/2506.09711

Non-Euclidean dual gradient ascent for entropically regularized linear and semidefinite programming
We present an optimization framework that exhibits dimension-independent convergence on a broad class of semidefinite programs (SDPs). Our approach first regularizes the primal problem with the von Neumann entropy, then solve the regularized problem using dual gradient ascent with respect to a problem-adapted norm. In particular, we show that the dual gradient norm converges to zero at a rate independent of the ambient dimension and, via rounding arguments, construct primal-feasible solutions i…

✅ Quick loop with my wife between some rain showers.
Feels so good to get out!
#cycling #BikeTooter #getoutside

Adversarial Training: Enhancing Out-of-Distribution Generalization for Learning Wireless Resource Allocation
Shengjie Liu, Chenyang Yang
https://arxiv.org/abs/2506.21208

Adversarial Training: Enhancing Out-of-Distribution Generalization for Learning Wireless Resource Allocation
Deep neural networks (DNNs) have widespread applications for optimizing resource allocation. Yet, their performance is vulnerable to distribution shifts between training and test data, say channels. In this letter, we resort to adversarial training (AT) for enhancing out-of-distribution (OOD) generalizability of DNNs trained in unsupervised manner. We reformulate AT to capture the OOD degradation, and propose a one-step gradient ascent method for AT. The proposed method is validated by optimizi…

Replaced article(s) found for math.AC. https://arxiv.org/list/math.AC/new
[1/1]:
- Ascent and descent of Gorenstein homological properties
Jian Liu, Wei Ren

Eagles OT Lane Johnson believes he's still improving at 35: 'I'm getting close to maybe my peak' https://www.nfl.com/news/eagles-ot-lane-johnson-believes-he-s-still-improving-at-35-i-m-getting-close-t…

Replaced article(s) found for math.CO. https://arxiv.org/list/math.CO/new
[1/1]:
Pattern-avoiding modified ascent sequences
https://

Cutting Slack: Quantum Optimization with Slack-Free Methods for Combinatorial Benchmarks
Monit Sharma, Hoong Chuin Lau
https://arxiv.org/abs/2507.12159 htt…

Cutting Slack: Quantum Optimization with Slack-Free Methods for Combinatorial Benchmarks
Constraint handling remains a key bottleneck in quantum combinatorial optimization. While slack-variable-based encodings are straightforward, they significantly increase qubit counts and circuit depth, challenging the scalability of quantum solvers. In this work, we investigate a suite of Lagrangian-based optimization techniques including dual ascent, bundle methods, cutting plane approaches, and augmented Lagrangian formulations for solving constrained combinatorial problems on quantum simulat…

SoK: Machine Unlearning for Large Language Models
Jie Ren, Yue Xing, Yingqian Cui, Charu C. Aggarwal, Hui Liu
https://arxiv.org/abs/2506.09227 https://

SoK: Machine Unlearning for Large Language Models
Large language model (LLM) unlearning has become a critical topic in machine learning, aiming to eliminate the influence of specific training data or knowledge without retraining the model from scratch. A variety of techniques have been proposed, including Gradient Ascent, model editing, and re-steering hidden representations. While existing surveys often organize these methods by their technical characteristics, such classifications tend to overlook a more fundamental dimension: the underlying…

Replaced article(s) found for physics.class-ph. https://arxiv.org/list/physics.class-ph/new
[1/1]:
- On minimizing cyclists' ascent times: Part II
Len Bos, Michael A. Slawinski, Rapha\"el A. Slawinski, Theodore Stanoev

Replaced article(s) found for physics.chem-ph. https://arxiv.org/list/physics.chem-ph/new/
[1/1]:
Steepest-Entropy-Ascent Framework for Predicting Arsenic Adsorption on Graphene Oxide Surfaces --...

Reusing Trajectories in Policy Gradients Enables Fast Convergence
Alessandro Montenegro, Federico Mansutti, Marco Mussi, Matteo Papini, Alberto Maria Metelli
https://arxiv.org/abs/2506.06178

Reusing Trajectories in Policy Gradients Enables Fast Convergence
Policy gradient (PG) methods are a class of effective reinforcement learning algorithms, particularly when dealing with continuous control problems. These methods learn the parameters of parametric policies via stochastic gradient ascent, typically using on-policy trajectory data to estimate the policy gradient. However, such reliance on fresh data makes them sample-inefficient. Indeed, vanilla PG methods require $O(ε^{-2})$ trajectories to reach an $ε$-approximate stationary point. A common …

On local rings of finite syzygy representation type
Souvik Dey, Kaito Kimura, Jian Liu, Yuya Otake
https://arxiv.org/abs/2507.17097 https://arxiv.org/pdf/2…

On local rings of finite syzygy representation type
Let R be a commutative Noetherian local ring. We give a characterization of when the completion of R has an isolated singularity. This result simultaneously improves a theorem of Dao and Takahashi and a theorem of Bahlekeh, Hakimian, Salarian, and Takahashi. As an application, we strengthen the Auslander-Huneke-Leuschke-Wiegand theorem in the form refined by Dao and Takahashi. We further investigate the ascent and descent of finite and countable syzygy representation type along the canonical ma…

Now this was a nice loop around the #chiemsee! 😊
#cycling #mountainbiking #mtb