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This paper presents a discrete-time nonlinear system identification method while satisfying the stability and safety properties of the system with high probability. An Extreme Learning Machine (ELM) is used with a Gaussian assumption on the…

Systems and Control · Electrical Eng. & Systems 2022-10-04 Iman Salehi , Tyler Taplin , Ashwin P. Dani

Recent work has generalized several results concerning the well-understood spiked Wigner matrix model of a low-rank signal matrix corrupted by additive i.i.d. Gaussian noise to the inhomogeneous case, where the noise has a variance profile.…

Statistics Theory · Mathematics 2025-10-10 Debsurya De , Dmitriy Kunisky

Semantic segmentation models trained on known object classes often fail in real-world autonomous driving scenarios by confidently misclassifying unknown objects. While pixel-wise out-of-distribution detection can identify unknown objects,…

Computer Vision and Pattern Recognition · Computer Science 2025-08-04 Marc Hölle , Walter Kellermann , Vasileios Belagiannis

The importance of the theory of pseudo-differential operators in the study of non linear integrable systems is point out. Principally, the algebra $\Xi $ of nonlinear (local and nonlocal) differential operators, acting on the ring of…

Mathematical Physics · Physics 2009-12-22 M. B. Sedra

We give a unateness tester for functions of the form $f:[n]^d\rightarrow R$, where $n,d\in \mathbb{N}$ and $R\subseteq \mathbb{R}$ with query complexity $O(\frac{d\log (\max(d,n))}{\epsilon})$. Previously known unateness testers work only…

Data Structures and Algorithms · Computer Science 2016-08-30 Roksana Baleshzar , Meiram Murzabulatov , Ramesh Krishnan S. Pallavoor , Sofya Raskhodnikova

The usefulness of time-frequency analysis methods in the study of quasicrystals was pointed out in a previous paper, where we proved that a tempered distribution $\mu$ on ${\mathbb R}^d$ whose Wigner transform is a measure supported on the…

Functional Analysis · Mathematics 2024-05-06 Paolo Boggiatto , Carmen Fernández , Antonio Galbis , Alessandro Oliaro

Given samples from two distributions over an $n$-element set, we wish to test whether these distributions are statistically close. We present an algorithm which uses sublinear in $n$, specifically, $O(n^{2/3}\epsilon^{-8/3}\log n)$,…

Data Structures and Algorithms · Computer Science 2010-11-05 Tugkan Batu , Lance Fortnow , Ronitt Rubinfeld , Warren D. Smith , Patrick White

Functions with low c-differential uniformity have optimal resistance to some types of differential cryptanalysis. In this paper, we investigate the c-differential uniformity of power functions over finite fields. Based on some known almost…

Information Theory · Computer Science 2020-08-28 Zhengbang Zha , Lei Hu

We consider the minimal k-grouping problem: given a graph G=(V,E) and a constant k, partition G into subgraphs of diameter no greater than k, such that the union of any two subgraphs has diameter greater than k. We give a silent…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-07-26 Ajoy K. Datta , Lawrence L. Larmore , Toshimitsu Masuzawa , Yuichi Sudo

The modulating functions method has been used for the identification of linear and nonlinear systems. In this paper, we generalize this method to the on-line identification of fractional order systems based on the Riemann-Liouville…

Numerical Analysis · Mathematics 2013-03-18 Da-Yan Liu , Taous-Meriem Laleg-Kirati , Olivier Gibaru , Wilfrid Perruquetti

Phase reduction theory has been applied to many systems with limit cycles; however, it has limited applications in incompressible fluid systems. This is because the calculation of the phase sensitivity function, one of the fundamental…

Fluid Dynamics · Physics 2019-06-12 Makoto Iima

We study the problem of learning k-juntas given access to examples drawn from a number of different product distributions. Thus we wish to learn a function f : {-1,1}^n -> {-1,1} that depends on k (unknown) coordinates. While the best known…

Machine Learning · Computer Science 2008-04-25 Jan Arpe , Elchanan Mossel

We prove several results giving new and stronger connections between learning, circuit lower bounds and pseudorandomness. Among other results, we show a generic learning speedup lemma, equivalences between various learning models in the…

Computational Complexity · Computer Science 2016-11-07 Igor C. Oliveira , Rahul Santhanam

We show that all non-negative submodular functions have high {\em noise-stability}. As a consequence, we obtain a polynomial-time learning algorithm for this class with respect to any product distribution on $\{-1,1\}^n$ (for any constant…

Machine Learning · Computer Science 2011-06-14 Mahdi Cheraghchi , Adam Klivans , Pravesh Kothari , Homin K. Lee

In the setting of error-correcting codes with feedback, Alice wishes to communicate a $k$-bit message $x$ to Bob by sending a sequence of bits over a channel while noiselessly receiving feedback from Bob. It has been long known (Berlekamp,…

Information Theory · Computer Science 2022-12-14 Meghal Gupta , Venkatesan Guruswami , Rachel Yun Zhang

In real-world applications, one often encounters ambiguously labeled data, where different annotators assign conflicting class labels. Partial-label learning allows training classifiers in this weakly supervised setting, where…

Machine Learning · Computer Science 2025-10-27 Tobias Fuchs , Florian Kalinke , Klemens Böhm

We revisit the Fourier transform of a Hankel function, of considerable importance in the theory of knife edge diffraction. Our approach is based directly upon the underlying Bessel equation, which admits manipulation into an alternate…

General Mathematics · Mathematics 2021-12-21 J. A. Grzesik

We describe a new model of massless thermal bosons which predicts an hyperbolic fluctuation spectrum at low frequencies. It is found that the partition function per mode is the Euler generating function for unrestricted partitions $p(n)$.…

Mathematical Physics · Physics 2009-11-10 Michel Planat

It is widely accepted that noisy quantum devices are limited to logarithmic depth circuits unless mid-circuit measurements and error correction are employed. However, this conclusion holds only for unital error channels, such as…

Quantum Physics · Physics 2024-11-08 Oles Shtanko , Kunal Sharma

A function from sequences to their subsequences is called selection function. A selection function is called admissible (with respect to normal numbers) if for all normal numbers, their subsequences obtained by the selection function are…

Information Theory · Computer Science 2011-02-17 Hayato Takahashi
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