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We study generalized permutohedra and supermodular functions. Specifically we analyze decomposability and irreducibility for these objects and establish some asymptotic behavior. We also study a related problem on irreducibility for…

Combinatorics · Mathematics 2023-03-13 Milan Haiman , Yuan Yao

Transformer-based language models have demonstrated impressive capabilities across a range of complex reasoning tasks. Prior theoretical work exploring the expressive power of transformers has shown that they can efficiently perform…

Machine Learning · Computer Science 2025-05-30 Zixuan Wang , Eshaan Nichani , Alberto Bietti , Alex Damian , Daniel Hsu , Jason D. Lee , Denny Wu

Obtaining meaningful solutions for inverse problems has been a major challenge with many applications in science and engineering. Recent machine learning techniques based on proximal and diffusion-based methods have shown promising results.…

Machine Learning · Computer Science 2024-02-08 Moshe Eliasof , Eldad Haber , Eran Treister

A solution is proposed for the problem of composition of ordinary generating functions. A new class of functions that provides a composition of ordinary generating functions is introduced; main theorems are presented; compositae are written…

Combinatorics · Mathematics 2010-09-15 Kruchinin Vladimir Victorovich

Polymers that extend covalently in two dimensions have attracted recent attention as a means of combining the mechanical strength and in-plane energy conduction of conventional two-dimensional (2D) materials with the low densities,…

Dual resonance is one of the great miracles of string theory. At a fundamental level, it implies that the particles exchanged in different channels are subtly equivalent. Furthermore, it is inextricably linked to the property of…

High Energy Physics - Theory · Physics 2023-10-16 Clifford Cheung , Grant N. Remmen

This work investigates efficient routes to turbulence in quasi-two-dimensional shear flows. Two-dimensional disturbances require high Reynolds numbers to incite transition from a steady base flow, as transient growth is modest. With the…

Fluid Dynamics · Physics 2025-02-04 Christopher J. Camobreco , Alban Pothérat , Gregory J. Sheard

Deep learning is regarded as a promising solution for reversible steganography. There is an accelerating trend of representing a reversible steo-system by monolithic neural networks, which bypass intermediate operations in traditional…

Multimedia · Computer Science 2023-03-08 Ching-Chun Chang , Xu Wang , Sisheng Chen , Isao Echizen , Victor Sanchez , Chang-Tsun Li

Superconducting circuits consisting of a few low-anharmonic transmons coupled to readout and bus resonators can perform basic quantum computations. Since the number of qubits in such circuits is limited to not more than a few tens, the…

Mesoscale and Nanoscale Physics · Physics 2019-07-18 Mohammad H. Ansari

The mathematical model representing the equation of motion of a pendulum is nonlinear. Solutions that satisfy the equation cannot be represented by elementary functions, such as trigonometric functions. To solve such problems, it is common…

Classical Physics · Physics 2019-02-19 Kazunori Shinohara

Recurrent neural networks are effective models to process sequences. However, they are unable to learn long-term dependencies because of their inherent sequential nature. As a solution, Vaswani et al. introduced the Transformer, a model…

Machine Learning · Computer Science 2023-03-28 Quentin Fournier , Gaétan Marceau Caron , Daniel Aloise

We formulate a new information-theoretic principle--the shifted composition rule--which bounds the divergence (e.g., Kullback-Leibler or R\'enyi) between the laws of two stochastic processes via the introduction of auxiliary shifts. In this…

Probability · Mathematics 2023-11-27 Jason M. Altschuler , Sinho Chewi

Standard Transformers have a fixed computational depth, fundamentally limiting their ability to generalize to tasks requiring variable-depth reasoning, such as multi-hop graph traversal or nested logic. We propose a depth-recurrent…

Machine Learning · Computer Science 2026-03-24 Hung-Hsuan Chen

Nonparametric extension of tensor regression is proposed. Nonlinearity in a high-dimensional tensor space is broken into simple local functions by incorporating low-rank tensor decomposition. Compared to naive nonparametric approaches, our…

Machine Learning · Statistics 2016-03-09 Masaaki Imaizumi , Kohei Hayashi

Neural networks are widely used as a model for classification in a large variety of tasks. Typically, a learnable transformation (i.e. the classifier) is placed at the end of such models returning a value for each class used for…

Machine Learning · Computer Science 2021-03-30 Federico Pernici , Matteo Bruni , Claudio Baecchi , Alberto Del Bimbo

This work is devoted to the study of the decay of multiscale deterministic solutions of the unforced Burgers' equation in the limit of vanishing viscosity. A deterministic model of turbulence-like evolution is considered. We con- struct the…

Fluid Dynamics · Physics 2009-11-06 S. N. Gurbatov , A. V. Troussov

This paper proposes a definition of recognizable transducers over monads and comonads, which bridges two important ongoing efforts in the current research on regularity. The first effort is the study of regular transductions, which extends…

Formal Languages and Automata Theory · Computer Science 2024-07-04 Rafał Stefański

Regular functions from infinite words to infinite words can be equivalently specified by MSO-transducers, streaming $\omega$-string transducers as well as deterministic two-way transducers with look-ahead. In their one-way restriction, the…

Formal Languages and Automata Theory · Computer Science 2024-09-19 V. Dave , E. Filiot , S. Krishna , N. Lhote

A system of commutative hyperbolic complex numbers in 2 dimensions is studied in this paper. Exponential and trigonometric forms are obtained for these hyperbolic twocomplex numbers. Expressions are given for the elementary functions of…

Complex Variables · Mathematics 2007-05-23 Silviu Olariu

In reactive synthesis, the goal is to automatically generate an implementation from a specification of the reactive and non-terminating input/output behaviours of a system. Specifications are usually modelled as logical formulae or automata…

Formal Languages and Automata Theory · Computer Science 2023-06-22 Léo Exibard , Emmanuel Filiot , Pierre-Alain Reynier