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This work investigates a reduced-complexity adaptive methodology to consensus tracking for a team of uncertain high-order nonlinear systems with switched (possibly asynchronous) dynamics. It is well known that high-order nonlinear systems…

Multiagent Systems · Computer Science 2020-06-11 Maolong Lv , Wenwu Yu , Jinde Cao , Simone Baldi

Data races are a notorious problem in parallel programming. There has been great research interest in type systems that statically prevent data races. Despite the progress in the safety and usability of these systems, lots of existing…

Programming Languages · Computer Science 2023-09-15 Yichen Xu , Aleksander Boruch-Gruszecki , Martin Odersky

Predictive coding (PC) is an influential theory of information processing in the brain, providing a biologically plausible alternative to backpropagation. It is motivated in terms of Bayesian inference, as hidden states and parameters are…

Coded distributed computing (CDC) introduced by Li et. al. is an effective technique to trade computation load for communication load in a MapReduce framework. CDC achieves an optimal trade-off by duplicating map computations at $r$…

Information Theory · Computer Science 2019-03-04 Nicholas Woolsey , Rong-Rong Chen , Mingyue Ji

This paper considers linear discrete-time systems with additive disturbances, and designs a Model Predictive Control (MPC) law to minimise a quadratic cost function subject to a chance constraint. The chance constraint is defined as a…

Systems and Control · Computer Science 2020-07-15 Shuhao Yan , Paul Goulart , Mark Cannon

Computer systems have evolved over the years starting from sizable, single-user, slow, and expensive machines to multi-user, fast, cheaper, and small-sized machines. The use of multi-user computer networks has given rise to a new paradigm…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-02-09 Aneesh Khole , Atharva Thakar , Avadhoot Kulkarni , Hrithik Jadhav , Shreyas Shende , Varad Karajkhede

Coded distributed computing (CDC) introduced by Li et al. in 2015 offers an efficient approach to trade computing power to reduce the communication load in general distributed computing frameworks such as MapReduce. For the more general…

Information Theory · Computer Science 2019-01-24 Nicholas Woolsey , Rong-Rong Chen , Mingyue Ji

Discriminatory Processor Sharing policy introduced by Kleinrock is of a great interest in many application areas, including telecommunications, web applications and TCP flow modelling. Under the DPS policy the job priority is controlled by…

Networking and Internet Architecture · Computer Science 2008-12-18 Natalia Osipova

With the advent of standards for deterministic network behavior, synthesizing network designs under delay constraints becomes the natural next task to tackle. Network Calculus (NC) has become a key method for validating industrial networks,…

Networking and Internet Architecture · Computer Science 2023-07-27 Fabien Geyer , Steffen Bondorf

We consider the problem of private linear computation (PLC) in a distributed storage system. In PLC, a user wishes to compute a linear combination of $f$ messages stored in noncolluding databases while revealing no information about the…

Information Theory · Computer Science 2021-06-29 Sarah A. Obead , Hsuan-Yin Lin , Eirik Rosnes , Jörg Kliewer

In large scale distributed computing systems, communication overhead is one of the major bottlenecks. In the map-shuffle-reduce framework, which is one of the major distributed computing frameworks, the communication load among servers can…

Information Theory · Computer Science 2020-05-14 Shunsuke Horii

As the use of differential privacy (DP) becomes widespread, the development of effective tools for reasoning about the privacy guarantee becomes increasingly critical. In pursuit of this goal, we demonstrate novel relationships between DP…

Cryptography and Security · Computer Science 2025-07-15 Zeki Kazan , Sagar Sharma , Wanrong Zhang , Bo Jiang , Qiang Yan

Semidefinite Programming (SDP) provides tight lower bounds for Optimal Power Flow problems. However, solving large-scale SDP problems requires exploiting sparsity. In this paper, we experiment several clique decomposition algorithms that…

Optimization and Control · Mathematics 2019-12-20 Julie Sliwak , Miguel Anjos , Lucas Létocart , Jean Maeght , Emiliano Traversi

The partitioning problem is of central relevance for designing and implementing non-centralized Model Predictive Control (MPC) strategies for large-scale systems. These control approaches include decentralized MPC, distributed MPC,…

Systems and Control · Electrical Eng. & Systems 2025-09-16 Alessandro Riccardi , Luca Laurenti , Bart De Schutter

In this paper, we introduce the general concept of coded power control (CPC) in a particular setting of the interference channel. Roughly, the idea of CPC consists in embedding information (about a random state) into the transmit power…

Information Theory · Computer Science 2014-05-28 Benjamin Larrousse , Samson Lasaulce

The concept of Probability of Causation (PC) is critically important in legal contexts and can help in many other domains. While it has been around since 1986, current operationalizations can obtain only the minimum and maximum values of…

Methodology · Statistics 2018-08-14 Tapajit Dey , Audris Mockus

The emerging computing continuum paves the way for exploiting multiple computing devices, ranging from the edge to the cloud, to implement the control algorithm. Different computing units over the continuum are characterized by different…

Systems and Control · Electrical Eng. & Systems 2025-03-11 Xiyu Gu , Matthias Pezzutto , Luca Schenato , Subhrakanti Dey

We investigate the performance on phoneme categorization and phoneme and word segmentation of several self-supervised learning (SSL) methods based on Contrastive Predictive Coding (CPC). Our experiments show that with the existing…

A myriad of applications ranging from engineering and scientific simulations, image and signal processing as well as high-sensitive data retrieval demand high processing power reaching up to teraflops for their efficient execution. While a…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-08-02 Patrick Mukala

This paper studies the distributed linearly separable computation problem, which is a generalization of many existing distributed computing problems such as distributed gradient descent and distributed linear transform. In this problem, a…

Information Theory · Computer Science 2020-10-06 Kai Wan , Hua Sun , Mingyue Ji , Giuseppe Caire