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This paper examines a discrete-time queuing system with applications to telecommunications traffic. The arrival process is a particular Markov modulated process which belongs to the class of discrete batched Markovian arrival processes. The…

Probability · Mathematics 2013-03-28 Richard G. Clegg

Machine unlearning (MU) aims to remove the influence of certain data points from a trained model without costly retraining. Most practical MU algorithms are only approximate and their performance can only be assessed empirically. Care must…

Machine Learning · Computer Science 2026-01-01 Jamie Lanyon , Axel Finke , Petros Andreou , Georgina Cosma

We present shared-memory parallel methods for Maximal Clique Enumeration (MCE) from a graph. MCE is a fundamental and well-studied graph analytics task, and is a widely used primitive for identifying dense structures in a graph. Due to its…

Data Structures and Algorithms · Computer Science 2020-01-30 Apurba Das , Seyed-Vahid Sanei-Mehri , Srikanta Tirthapura

Data movement is becoming the dominant contributor to the time and energy costs of computation across a wide range of application domains. However, time complexity is inadequate to analyze data movement. This work expands upon Data Movement…

Data Structures and Algorithms · Computer Science 2022-03-08 Wesley Smith , Aidan Goldfarb , Chen Ding

Massively-parallel graph algorithms have received extensive attention over the past decade, with research focusing on three memory regimes: the superlinear regime, the near-linear regime, and the sublinear regime. The sublinear regime is…

Data Structures and Algorithms · Computer Science 2023-03-01 Orr Fischer , Adi Horowitz , Rotem Oshman

We present a new model for distributed shared memory systems, based on remote data accesses. Such features are offered by network interface cards that allow one-sided operations, remote direct memory access and OS bypass. This model leads…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-03-17 Franck Butelle , Camille Coti

Machine unlearning (MU) is becoming a promising paradigm to achieve the "right to be forgotten", where the training trace of any chosen data points could be eliminated, while maintaining the model utility on general testing samples after…

Machine Learning · Computer Science 2024-10-22 Junjie Chen , Qian Chen , Jian Lou , Xiaoyu Zhang , Kai Wu , Zilong Wang

In the classical RAM, we have the following useful property. If we have an algorithm that uses $M$ memory cells throughout its execution, and in addition is sparse, in the sense that, at any point in time, only $m$ out of $M$ cells will be…

Quantum Physics · Physics 2022-12-22 Harry Buhrman , Bruno Loff , Subhasree Patro , Florian Speelman

We propose and implement a priority queue suitable for use in event driven molecular dynamics simulations. All operations on the queue take on average O(1) time per collision. In comparison, previously studied queues for event driven…

Computational Physics · Physics 2015-06-26 Gerald Paul

We present data-oblivious algorithms in the external-memory model for compaction, selection, and sorting. Motivation for such problems comes from clients who use outsourced data storage services and wish to mask their data access patterns.…

Data Structures and Algorithms · Computer Science 2011-03-29 Michael T. Goodrich

Quorum systems are a common way to formalize failure assumptions in distributed systems. Traditionally, these assumptions are shared by all involved processes. More recently, systems have emerged which allow processes some freedom in…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-09-17 Michael Senn , Christian Cachin

In this paper, we analyze a retrial queueing system with Batch Markovian Arrival Processes and two types of customers. The rate of individual repeated attempts from the orbit is modulated according to a Markov Modulated Poisson Process.…

Probability · Mathematics 2015-04-07 Jinbiao Wu , Yi Peng , Zaiming Liu

The recent advent of programmable switches makes distributed algorithms readily deployable in real-world datacenter networks. However, there are still gaps between theory and practice that prevent the smooth adaptation of CONGEST algorithms…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-06-16 Ran Ben Basat , Keren Censor-Hillel , Yi-Jun Chang , Wenchen Han , Dean Leitersdorf , Gregory Schwartzman

Distributed quantum computing (DQC) has emerged as a promising approach to overcome the scalability limitations of monolithic quantum processors in terms of computational capability. However, realising the full potential of DQC requires…

Serial and parallel algorithms for simulation of tandem queueing systems with infinite buffers are presented, and their performance is examined. It is shown that the algorithms which are based on a simple computational procedure involve low…

Numerical Analysis · Mathematics 2012-10-25 Sergei M. Ermakov , Nikolai K. Krivulin

Despite widespread interest in multicore computing, concur- rency models in mainstream languages often lead to subtle, error-prone code. Observationally Cooperative Multithreading (OCM) is a new approach to shared-memory parallelism.…

This paper studies a generalized busy-time scheduling model on heterogeneous machines. The input to the model includes a set of jobs and a set of machine types. Each job has a size and a time interval during which it should be processed.…

Data Structures and Algorithms · Computer Science 2021-05-14 Mozhengfu Liu , Xueyan Tang

Growing power dissipation due to high performance requirement of processor suggests multicore processor technology, which has become the technology for present and next decade. Research advocates asymmetric multi-core processor system for…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-02-15 Alan David

We consider the classical problem of representing a collection of priority queues under the operations \Findmin{}, \Insert{}, \Decrease{}, \Meld{}, \Delete{}, and \Deletemin{}. In the comparison-based model, if the first four operations are…

Data Structures and Algorithms · Computer Science 2011-12-06 Amr Elmasry , Jyrki Katajainen

Mixture Markov Model (MMM) is a widely used tool to cluster sequences of events coming from a finite state-space. However the MMM likelihood being multi-modal, the challenge remains in its maximization. Although Expectation-Maximization…

Optimization and Control · Mathematics 2026-04-16 Priyam Das , Deborshee Sen , Debsurya De , Jue Hou , Zahra S. H. Abad , Nicole Kim , Zongqi Xia , Tianxi Cai
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