Tootfinder

CNN Security Analyst Defends Kristi Noem and Agents Who Shoved Senator Out of Presser (Joe DePaolo/Mediaite)
https://www.mediaite.com/media/news/cnn-security-analyst-defends-kristi-noem-and-agents-who-shoved-senator-out-of-presser/
http://www.memeorandum.com/250612/p123#a250612p123

A discontinuous Galerkin plane wave neural network method for Helmholtz equation and Maxwell's equations
Long Yuan, Menghui Wu, Qiya Hu
https://arxiv.org/abs/2506.09309

A discontinuous Galerkin plane wave neural network method for Helmholtz equation and Maxwell's equations
In this paper we propose a discontinuous Galerkin plane wave neural network (DGPWNN) method for approximately solving Helmholtz equation and Maxwell's equations. In this method, we define an elliptic-type variational problem as in the plane wave least square method with $h-$refinement and introduce the adaptive construction of recursively augmented discontinuous Galerkin subspaces whose basis functions are realizations of element-wise neural network functions with $hp-$refinement, where the act…

The Intrinsic Riemannian Proximal Gradient Method for Nonconvex Optimization
Ronny Bergmann, Hajg Jasa, Paula John, Max Pfeffer
https://arxiv.org/abs/2506.09775

The Intrinsic Riemannian Proximal Gradient Method for Nonconvex Optimization
We consider the proximal gradient method on Riemannian manifolds for functions that are possibly not geodesically convex. Starting from the forward-backward-splitting, we define an intrinsic variant of the proximal gradient method that uses proximal maps defined on the manifold and therefore does not require or work in the embedding. We investigate its convergence properties and illustrate its numerical performance, particularly for nonconvex or nonembedded problems that are hence out of reach …

'Political Theater!' Kristi Noem Blames Senator Padilla for Getting Himself Manhandled By Agents in Stunning Fox News Interview (Joe DePaolo/Mediaite)
https://www.mediaite.com/media/news/political-theater-kristi-noem-blames-senator-padilla-for-getting-himself-manhandled-by-agents-in-stunning-fox-news-interview/
http://www.memeorandum.com/250612/p119#a250612p119

A thorough study of Riemannian Newton's Method
Caio O. da Silva, Yuri A. Aoto, Felipe F. G. S. Costa, M\'arcio F. da Silva
https://arxiv.org/abs/2506.09297

A thorough study of Riemannian Newton's Method
This work presents a thorough numerical study of Riemannian Newton's Method (RNM) for optimization problems, with a focus on the Grassmannian and on the Stiefel manifold. We compare the Riemannian formulation of Newton's Method with its classical Euclidean counterpart based on Lagrange multipliers by applying both approaches to the important and challenging Hartree--Fock energy minimization problem from Quantum Chemistry. Experiments on a dataset of 125 molecules show that the Riemannian approa…

A Combined Parallel-in-time Direct Inverse (ParaDIn)-Parareal Method for Nonlinear Differential Equations
Subhash Paudel, Nail K. Yamaleev
https://arxiv.org/abs/2506.10820

A Combined Parallel-in-time Direct Inverse (ParaDIn)-Parareal Method for Nonlinear Differential Equations
As has been shown in our previous work, the parallel-in-time direct inverse (ParaDIn) method introduced by Yamaleev and Paudel in (arXiv: 2406.00878v1, 2024) imposes some constraint on the maximum number of time levels, $N_t$, that can be integrated in parallel. To circumvent this problem and further increase the speedup, we combine the ParaDIn method with the Parareal algorithm to efficiently parallelize the first-order time derivative term in nonlinear partial differential equations discretiz…

ASMOP: Additional sampling stochastic trust region method for multi-objective problems
Nata\v{s}a Krklec Jerinki\'c, Luka Rute\v{s}i\'c
https://arxiv.org/abs/2506.10976

ASMOP: Additional sampling stochastic trust region method for multi-objective problems
We consider an unconstrained multi-criteria optimization problem with finite sum objective functions. The proposed algorithm belongs to a non-monotone trust-region framework where additional sampling approach is used to govern the sample size and the acceptance of a candidate point. Depending on the problem, the method can result in a mini-batch or an increasing sample size approach. Therefore, this work can be viewed as an extension of additional sampling trust region method for scalar finite …

Bob Costas Condemns Mainstream Press for Doing 'MAGA Media': 'There Really Isn't Two Sides' (Michael Luciano/Mediaite)
https://www.mediaite.com/media/news/bob-costas-condemns-mainstream-press-for-doing-maga-media-there-really-isnt-two-sides/
http://www.memeorandum.com/250610/p152#a250610p152

Bregman proximal gradient method for linear optimization under entropic constraints
Luis M. Brice\~no-Arias, Ma\"el Le Treust
https://arxiv.org/abs/2506.10849

Bregman proximal gradient method for linear optimization under entropic constraints
In this paper, we present an efficient algorithm for solving a linear optimization problem with entropic constraints -- a class of problems that arises in game theory and information theory. Our analysis distinguishes between the cases of active and inactive constraints, addressing each using a Bregman proximal gradient method with entropic Legendre functions, for which we establish an ergodic convergence rate of $O(1/n)$ in objective values. For a specific cost structure, our framework provide…

Optimal Voltage Control Using Online Exponential Barrier Method
Peng Zhang, Baosen Zhang
https://arxiv.org/abs/2506.10247 https://arx…

Optimal Voltage Control Using Online Exponential Barrier Method
This paper address the optimal voltage control problem of distribution systems with high penetration of inverter-based renewable energy resources, under inaccurate model information. We propose the online exponential barrier method that explicitly leverages the online feedback from grids to enhance the robustness to model inaccuracy and incorporates the voltage constraints to maintain the safety requirements. We provide analytical results on the optimal barrier parameter selection and sufficien…