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The paradigm of layered networks is used to describe many real-world systems -- from biological networks, to social organizations and transportation systems. Recently there has been much progress in understanding the general properties of…

Physics and Society · Physics 2016-10-05 Márton Pósfai , Jianxi Gao , Sean P. Cornelius , Albert-László Barabási , Raissa M. D'Souza

Time series analysis is a field of data science which is interested in analyzing sequences of numerical values ordered in time. Time series are particularly interesting because they allow us to visualize and understand the evolution of a…

Machine Learning · Computer Science 2020-10-02 Hassan Ismail Fawaz

The kernel method is a potential approach to analyzing structured data such as sequences, trees, and graphs; however, unordered trees have not been investigated extensively. Kimura et al. (2011) proposed a kernel function for unordered…

Data Structures and Algorithms · Computer Science 2012-06-22 Daisuke Kimura , Hisashi Kashima

This paper proposes a parallelizable algorithm for linear-quadratic model predictive control (MPC) problems with state and input constraints. The algorithm itself is based on a parallel MPC scheme that has originally been designed for…

Optimization and Control · Mathematics 2022-07-04 Jiahe Shi , Yuning Jiang , Juraj Oravec , Boris Houska

This paper deals with design of maximum hands-off hybrid control sequences for discrete-time switched linear systems. It is a sparsest combination of a discrete control sequence (i.e. the switching sequence) and a continuous control…

Optimization and Control · Mathematics 2026-01-27 Darsana U , Atreyee Kundu

Inquiries such as whether a task A depends on a task B, whether an author A has been influenced by a paper B, whether a certain protein is associated with a specific biological process or molecular function, or whether class A inherits from…

Data Structures and Algorithms · Computer Science 2024-05-02 Giorgos Kritikakis , Ioannis G Tollis

In this work, we consider the problem of learning a feed-forward neural network controller to safely steer an arbitrarily shaped planar robot in a compact and obstacle-occluded workspace. Unlike existing methods that depend strongly on the…

Systems and Control · Electrical Eng. & Systems 2022-12-14 Panagiotis Vlantis , Leila J. Bridgeman , Michael M. Zavlanos

Markov Chain Monte Carlo (MCMC) algorithms are often used for approximate inference inside learning, but their slow mixing can be difficult to diagnose and the approximations can seriously degrade learning. To alleviate these issues, we…

Machine Learning · Computer Science 2015-02-25 Jacob Steinhardt , Percy Liang

The application considered is mixed-criticality scheduling. The core formal approaches used are Rely-Guarantee conditions and the Timeband framework; these are applied to give a layered description of job scheduling which includes…

Software Engineering · Computer Science 2022-07-15 Cliff B Jones , Alan Burns

This paper focuses on the analysis of real-time non preemptive multiprocessor scheduling with precedence and several latency constraints. It aims to specify a schedulability condition which enables a designer to check a priori -without…

Operating Systems · Computer Science 2013-01-22 Omar Kermia

Courcelle's famous theorem from 1990 states that any property of graphs definable in monadic second-order logic (MSO) can be decided in linear time on any class of graphs of bounded treewidth, or in other words, MSO is fixed-parameter…

Logic in Computer Science · Computer Science 2015-03-13 Stephan Kreutzer , Siamak Tazari

Structural symmetries of linear dynamical systems can be exploited for decoupling the dynamics and reducing the computational complexity of the controller implementation. However, in practical applications, inexact structural symmetries…

Systems and Control · Electrical Eng. & Systems 2023-07-03 Idris Kempf , Paul Goulart , Stephen Duncan

The objective of this paper is to study the controllability of discrete-time linear control systems in solvable Lie groups. In the special case of nilpotent Lie groups, a necessary and sufficient condition for controllability is…

Optimization and Control · Mathematics 2024-06-11 Thiago Cavalheiro , Alexandre Santana , João Cossich , Victor Ayala

A sequential training method for large-scale feedforward neural networks is presented. Each layer of the neural network is decoupled and trained separately. After the training is completed for each layer, they are combined together. The…

Machine Learning · Computer Science 2019-05-21 Jongrae Kim

Iterative learning control (ILC) is a control strategy for repetitive tasks wherein information from previous runs is leveraged to improve future performance. Optimization-based ILC (OB-ILC) is a powerful design framework for constrained…

Systems and Control · Electrical Eng. & Systems 2022-05-27 Dominic Liao-McPherson , Efe C. Balta , Alisa Rupenyan , John Lygeros

We study the secure decentralized Pliable Index CODing (PICOD) problem with circular side information sets at the users. The security constraint forbids every user to decode more than one message while a decentralized setting means there is…

Information Theory · Computer Science 2020-10-21 Tang Liu , Daniela Tuninetti

This paper studies the problem of controlling complex networks, that is, the joint problem of selecting a set of control nodes and of designing a control input to steer a network to a target state. For this problem (i) we propose a metric…

Systems and Control · Computer Science 2014-03-04 Fabio Pasqualetti , Sandro Zampieri , Francesco Bullo

Sequences with high linear complexity have wide applications in cryptography. In this paper, a new class of quaternary sequences over $\mathbb{F}_4$ with period $2p^mq^n$ is constructed using generalized cyclotomic classes. Results show…

Information Theory · Computer Science 2020-01-30 Qiuyan Wang , Chenhuang Wu , Minghui Yang , Yang Yan

This paper studies the structural controllability of a class of uncertain switched linear systems, where the parameters of subsystems state matrices are either unknown or zero. The structural controllability is a generalization of the…

Systems and Control · Computer Science 2013-08-27 Xiaomeng Liu , Hai Lin , Ben M. Chen

Despite the success of model predictive control (MPC), its application to high-dimensional systems, such as flexible structures and coupled fluid/rigid-body systems, remains a largely open challenge due to excessive computational…

Systems and Control · Computer Science 2019-05-03 Joseph Lorenzetti , Benoit Landry , Sumeet Singh , Marco Pavone
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