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Here the Integral Value Transformations (IVTs) are considered to be Discrete Dynamical System map in the space\mathbb{N}_(0). In this paper, the dynamics of IVTs is deciphered through the light of Topological Dynamics.

Discrete Mathematics · Computer Science 2011-07-07 Sk. S. Hassan , A. Roy , P. Pal. Choudhury , B. K. Nayak

A pattern class is a set of permutations closed under the formation of subpermutations. Such classes can be characterised as those permutations not involving a particular set of forbidden permutations. A simple collection of necessary and…

Combinatorics · Mathematics 2007-05-23 M. H. Albert , M. D. Atkinson , Robert Brignall

We investigate the issue of testing CPT invariance in the neutral-$D$ system, using $D$ events obtained either from fixed-target experiments or from a tau-charm factory. For both types of experiments we show that the expected suppression of…

High Energy Physics - Phenomenology · Physics 2009-09-25 Don Colladay , Alan Kostelecky

Many practical scenarios make it necessary to evaluate top-k queries over data items with partially unknown values. This paper considers a setting where the values are taken from a numerical domain, and where some partial order constraints…

Databases · Computer Science 2019-08-28 Antoine Amarilli , Yael Amsterdamer , Tova Milo , Pierre Senellart

A security policy specifies a security property as the maximal information flow. A distributed system composed of interacting processes implicitly defines an intransitive security policy by repudiating direct information flow between…

Cryptography and Security · Computer Science 2013-10-15 Jean Quilbeuf , Georgeta Igna , Denis Bytschkow , Harald Ruess

In constrained Markov decision processes (CMDPs) with adversarial rewards and constraints, a well-known impossibility result prevents any algorithm from attaining both sublinear regret and sublinear constraint violation, when competing…

Machine Learning · Computer Science 2024-09-27 Francesco Emanuele Stradi , Anna Lunghi , Matteo Castiglioni , Alberto Marchesi , Nicola Gatti

With the increasing interest in applying the methodology of difference-of-convex (dc) optimization to diverse problems in engineering and statistics, this paper establishes the dc property of many well-known functions not previously known…

Optimization and Control · Mathematics 2019-02-20 Maher Nouiehed , Jong-Shi Pang , Meisam Razaviyayn

This paper studies a basic model of a dynamical distribution network, where the network topology is given by a directed graph with storage variables corresponding to the vertices and flow inputs corresponding to the edges. We aim at…

Optimization and Control · Mathematics 2014-11-13 Jieqiang Wei , Arjan J. van der Schaft

Inspired by the human ability to learn and organize knowledge into hierarchical taxonomies with prototypes, this paper addresses key limitations in current deep hierarchical clustering methods. Existing methods often tie the structure to…

Computer Vision and Pattern Recognition · Computer Science 2025-10-01 Zekun Wang , Ethan Haarer , Tianyi Zhu , Zhiyi Dai , Christopher J. MacLellan

Contextual Bandits find important use cases in various real-life scenarios such as online advertising, recommendation systems, healthcare, etc. However, most of the algorithms use flat feature vectors to represent context whereas, in the…

Machine Learning · Computer Science 2021-06-29 Kaushik Roy , Qi Zhang , Manas Gaur , Amit Sheth

We study the problem of detecting a structured, low-rank signal matrix corrupted with additive Gaussian noise. This includes clustering in a Gaussian mixture model, sparse PCA, and submatrix localization. Each of these problems is…

Statistics Theory · Mathematics 2017-01-24 Jess Banks , Cristopher Moore , Nicolas Verzelen , Roman Vershynin , Jiaming Xu

A candidate explanation of the good empirical performance of deep neural networks is the implicit regularization effect of first order optimization methods. Inspired by this, we prove a convergence theorem for nonconvex composite…

Machine Learning · Computer Science 2023-02-14 Dávid Terjék , Diego González-Sánchez

Bioprocesses are often characterised by nonlinear and uncertain dynamics, posing particular challenges for model predictive control (MPC) algorithms due to their computational demands when applied to nonlinear systems. Recent advances in…

Optimization and Control · Mathematics 2025-02-05 Niels Krausch , Martin Doff-Sotta , Mark Cannon , Peter Neubauer , Mariano Nicolas Cruz Bournazou

Deep networks are able to learn highly predictive models of video data. Due to video length, a common strategy is to train them on small video snippets. We apply the deep Taylor / LRP technique to understand the deep network's…

Machine Learning · Computer Science 2018-06-20 Christopher Anders , Grégoire Montavon , Wojciech Samek , Klaus-Robert Müller

We study the problem of recognizing the cluster structure of a graph in the framework of property testing in the bounded degree model. Given a parameter $\varepsilon$, a $d$-bounded degree graph is defined to be $(k, \phi)$-clusterable, if…

Data Structures and Algorithms · Computer Science 2015-04-14 Artur Czumaj , Pan Peng , Christian Sohler

In this paper, we study a polynomial decomposition model that arises in problems of system identification, signal processing and machine learning. We show that this decomposition is a special case of the X-rank decomposition --- a powerful…

Information Theory · Computer Science 2017-04-07 Pierre Comon , Yang Qi , Konstantin Usevich

A type system is introduced for a generic Object Oriented programming language in order to infer resource upper bounds. A sound andcomplete characterization of the set of polynomial time computable functions is obtained. As a consequence,…

Programming Languages · Computer Science 2018-02-20 Emmanuel Hainry , Romain Péchoux

In science, macro level descriptions of the causal interactions within complex, dynamical systems are typically deemed convenient, but ultimately reducible to a complete causal account of the underlying micro constituents. Yet, such a…

Neurons and Cognition · Quantitative Biology 2020-04-02 Larissa Albantakis , Francesco Massari , Maggie Beheler-Amass , Giulio Tononi

Whitney type examples of maps $f\in C^k(\real^m,\real^n)$ for a maximal possible real $k$, and multidimensional space-filling curves with special properties are constructed.

Geometric Topology · Mathematics 2016-09-07 Azat Ainouline

We demonstrate how one may identify or constrain possible violation of $CP$, $T$ and $CPT$ symmetries in the $K^0$-$\bar{K^0}$ system in a way as phenomenological and comprehensive as possibie. For this purpose, we first introduce…

High Energy Physics - Phenomenology · Physics 2007-05-23 Y. Kouchi , A. Shinbori , Y. Takeuchi , S. Y. Tsai
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