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We prove in an elementary fashion that the image of a commutative monotone $\sigma$-complete $C^*$-algebra under a $\sigma$-normal morphism is again monotone $\sigma$-complete and give an application of this result in spectral theory.

Operator Algebras · Mathematics 2007-10-15 Marcel de Jeu

We introduce techniques for proving uniform termination of graph transformation systems, based on matrix interpretations for string rewriting. We generalize this technique by adapting it to graph rewriting instead of string rewriting and by…

Logic in Computer Science · Computer Science 2023-10-12 H. J. Sander Bruggink , Barbara König , Dennis Nolte , Hans Zantema

A simple \(P_\lambda\)-point on a regular cardinal \(\kappa\) is a uniform ultrafilter on \(\kappa\) with a mod-bounded decreasing generating sequence of length \(\lambda\). We prove that if there is a simple $P_\lambda$-point ultrafilter…

Logic · Mathematics 2025-12-10 Tom Benhamou , Gabriel Goldberg

Recently, it has been claimed that some complex networks are self-similar under a convenient renormalization procedure. We present a general method to study renormalization flows in graphs. We find that the behavior of some variables under…

Physics and Society · Physics 2009-11-13 Filippo Radicchi , José Javier Ramasco , Alain Barrat , Santo Fortunato

Let $M$ be a $\lambda$-indexed (that is, Jensen indexed) premouse. We prove that $M$ is iterable with respect to standard $\lambda$-iteration rules iff $M$ is iterable with respect to a natural version of Mitchell-Steel iteration rules.…

Logic · Mathematics 2021-01-12 Farmer Schlutzenberg

In this paper, we use composite optimization algorithms to solve sigmoid networks. We equivalently transfer the sigmoid networks to a convex composite optimization and propose the composite optimization algorithms based on the linearized…

Optimization and Control · Mathematics 2023-07-10 Huixiong Chen , Qi Ye

We study estimation of the covariance matrix under relative condition number loss $\kappa(\Sigma^{-1/2} \hat{\Sigma} \Sigma^{-1/2})$, where $\kappa(\Delta)$ is the condition number of matrix $\Delta$, and $\hat{\Sigma}$ and $\Sigma$ are the…

Statistics Theory · Mathematics 2018-10-18 David L. Donoho , Behrooz Ghorbani

We define a weak iterability notion that is sufficient for a number of arguments concerning $\Sigma_1$-definability at uncountable regular cardinals. In particular we give its exact consistency strength firstly in terms of the second…

Logic · Mathematics 2019-01-18 P. D. Welch

Fixed points of the 2d renormalization group flow are known to correspond to tree level string vacua. We discuss how the renormalization group (or "sigma model") approach can be extended to the string loop level. The central role of the…

High Energy Physics - Theory · Physics 2026-02-20 Arkady A. Tseytlin

Many optimization problems arising in high-dimensional statistics decompose naturally into a sum of several terms, where the individual terms are relatively simple but the composite objective function can only be optimized with iterative…

Optimization and Control · Mathematics 2016-06-30 Rina Foygel Barber , Emil Y. Sidky

Complex networks have acquired a great popularity in recent years, since the graph representation of many natural, social and technological systems is often very helpful to characterize and model their phenomenology. Additionally, the…

Physics and Society · Physics 2009-02-06 Filippo Radicchi , Alain Barrat , Santo Fortunato , Jose J. Ramasco

In bilevel and robust optimization we are concerned with combinatorial min-max problems, for example from the areas of min-max regret robust optimization, network interdiction, most vital vertex problems, blocker problems, and two-stage…

Computational Complexity · Computer Science 2025-11-24 Christoph Grüne , Lasse Wulf

The optimization version of the cavity method for single instances, called Max-Sum, has been applied in the past to the Minimum Steiner Tree Problem on Graphs and variants. Max-Sum has been shown experimentally to give asymptotically…

Data Structures and Algorithms · Computer Science 2016-08-03 Alfredo Braunstein , Anna Muntoni

A topological space $A$ is said to be compatible with a set $\Sigma$ of equations (involving operation symbols $F_t$) iff there are continuous operations $\overline F_t$ identically satisfying $\Sigma$ on $A$. The paper's main focus is on…

Rings and Algebras · Mathematics 2014-02-18 Walter Taylor

Normalization techniques have only recently begun to be exploited in supervised learning tasks. Batch normalization exploits mini-batch statistics to normalize the activations. This was shown to speed up training and result in better…

Machine Learning · Computer Science 2017-03-08 Mengye Ren , Renjie Liao , Raquel Urtasun , Fabian H. Sinz , Richard S. Zemel

In this Letter, we use a general renormalization-group algorithm to implement Propp and Wilson's "coupling from the past" approach to complex physical systems. Our algorithm follows the evolution of the entire configuration space under the…

Statistical Mechanics · Physics 2008-02-17 Cedric Chanal , Werner Krauth

In this work we introduce a new optimisation method called SAGA in the spirit of SAG, SDCA, MISO and SVRG, a set of recently proposed incremental gradient algorithms with fast linear convergence rates. SAGA improves on the theory behind SAG…

Machine Learning · Computer Science 2014-12-17 Aaron Defazio , Francis Bach , Simon Lacoste-Julien

We show that higher Sacks forcing at a regular limit cardinal and club Miller forcing at an uncountable regular cardinal both add a diamond sequence. We answer the longstanding question, whether $\kappa = \kappa^{<\kappa} \geq\aleph_1$…

Logic · Mathematics 2025-04-14 Heike Mildenberger , Saharon Shelah

We present the exact realization of the extended Snyder model. Using similarity transformations, we construct realizations of the original Snyder and the extended Snyder models. Finally, we present the exact new realization of the…

Mathematical Physics · Physics 2023-10-11 Tea Martinić Bilać , Stjepan Meljanac

Sampling from unnormalized densities using diffusion models has emerged as a powerful paradigm. However, while recent approaches that use least-squares `matching' objectives have improved scalability, they often necessitate significant…

Machine Learning · Computer Science 2026-03-03 Denis Blessing , Lorenz Richter , Julius Berner , Egor Malitskiy , Gerhard Neumann
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