Blar i ODA Open Digital Archive på forfatter "Yazidi, Anis"

Viser treff 41-60 av 157

    • Distributed learning automata-based scheme for classification using novel pursuit scheme 

      Goodwin, Morten; Yazidi, Anis (Applied intelligenc;volume 50, issue 7, Peer reviewed; Journal article, 2020-03-02)
      Learning Automata (LA) is a popular decision making mechanism to “determine the optimal action out of a set of allowable actions” (Agache and Oommen, IEEE Trans Syst Man Cybern-Part B Cybern 2002(6): 738–749, 2002). The ...

    • DoS and DDoS mitigation using Variational Autoencoders 

      Bårli, Eirik Molde; Yazidi, Anis; Viedma, Enrique Herrera; Haugerud, Hårek (Computer Networks;Volume 199, 9 November 2021, 108399, Peer reviewed; Journal article, 2021-09-01)
      DoS and DDoS attacks have been growing in size and number over the last decade and existing solutions to mitigate these attacks are largely inefficient. Compared to other types of malicious cyber attacks, DoS and DDoS ...

    • A dynamic and scalable parallel Network Intrusion Detection System using intelligent rule ordering and Network Function Virtualization 

      Haugerud, Hårek; Tran, Huy Nhut; Aitsaadi, Nadjib; Yazidi, Anis (Future generations computer systems;Volume 124, November 2021, Peer reviewed; Journal article, 2021-06-12)
      A Network Intrusion Detection System (NIDS) is a fundamental security tool. However, under heavy network traffic, a NIDS might become a bottleneck. In an overloaded state, incoming and outgoing packets in the network might ...

    • Dynamic Ordering of Firewall Rules Using a Novel Swapping Window-based Paradigm 

      Mohan, Ratish; Yazidi, Anis; Feng, Boning; Oommen, John (Peer reviewed; Chapter, 2016)
      Designing and implementing efficient firewall strategies in the age of the Internet of Things (IoT) is far from trivial. This is because, as time proceeds, an increasing number of devices will be connected, accessed and ...

    • The Dynamical Landscape of Reservoir Computing with Elementary Cellular Automata 

      Glover, Tom Eivind; Lind, Pedro; Yazidi, Anis; Osipov, Evgeny; Nichele, Stefano (Conference object, 2021)
      Reservoir Computing with Cellular Automata (ReCA) is a promising concept by virtue of its potential for efficient hardware implementation and theoretical understanding of Cellular Auotmata (CA). However, ReCA has so far ...

    • Edge information based image fusion metrics using fractional order differentiation and sigmoidal functions 

      Sengupta, Animesh; Seal, Ayan; Krejcar, Ondrej; Yazidi, Anis (IEEE Access;Volume: 8, Journal article; Peer reviewed, 2020)
      In recent years, the number of image fusion schemes presented by the research community has increased significantly. Measuring the performance of these schemes is an important issue. In this work, we introduce three ...

    • Effective live migration of virtual machines using partitioning and affinity aware-scheduling 

      Yazidi, Anis; Ung, Fredrik; Haugerud, Hårek; Begnum, Kyrre (Computers and Electrical Engineering;volume 69 (2018), Journal article; Peer reviewed, 2018-07-11)
      During maintenance and disaster recovery scenarios, Virtual Machine (VM) inter-site migrations usually take place over limited bandwidth—typically Wide Area Network (WAN)—which is highly affected by the amount of inter-VM ...

    • Efficient quantile tracking using an oracle 

      Hammer, Hugo Lewi; Yazidi, Anis; Riegler, Michael; Rue, Håvard (Applied intelligence (Boston);, Peer reviewed; Journal article, 2022-04-14)
      Concept drift is a well-known issue that arises when working with data streams. In this paper, we present a procedure that allows a quantile tracking procedure to cope with concept drift. We suggest using expected quantile ...

    • Efficient Tracking of Statistical Properties of Data Streams with Rapid Changes 

      Hammer, Hugo Lewi; Yazidi, Anis (The 26th Mediterranean Conference on Control and Automation;, Chapter; Chapter; Peer reviewed, 2018-08-23)
      Many real-life dynamical systems change rapidly followed by almost stationary periods. In this paper, we consider streams of data with such rapidly changing behavior and investigate the problem of tracking their statistical ...

    • Energy Efficient Target Coverage in Wireless Sensor Networks Using Adaptive Learning 

      Rauniyar, Ashish; Kunwar, Jeevan; Haugerud, Hårek; Yazidi, Anis; Engelstad, Paal E. (Communications in Computer and Information Science;volume 1130, Journal article; Peer reviewed; Book chapter, 2019)
      Over the past few years, innovation in the development of Wireless Sensor Networks (WSNs) has evolved rapidly. WSNs are being used in many application fields such as target coverage, battlefield surveillance, home security, ...

    • Enhanced Equivalence Projective Simulation: A Framework for Modeling Formation of Stimulus Equivalence Classes 

      Abolpour Mofrad, Asieh; Yazidi, Anis; Abolpour Mofrad, Samaneh; Hammer, Hugo Lewi; Arntzen, Erik (Neural Computation;Vol. 33, No. 2, Journal article; Peer reviewed, 2021-02-01)
      Formation of stimulus equivalence classes has been recently modeled through equivalence projective simulation (EPS), a modified version of a projective simulation (PS) learning agent. PS is endowed with an episodic memory ...

    • Equivalence Projective Simulation as a Framework for Modeling Formation of Stimulus Equivalence Classes 

      Abolpour Mofrad, Asieh; Yazidi, Anis; Hammer, Hugo Lewi; Arntzen, Erik (Neural Computation;Volume 32, No. 5, Journal article; Peer reviewed, 2020-04-14)
      Stimulus equivalence (SE) and projective simulation (PS) study complex behavior, the former in human subjects and the latter in artificial agents. We apply the PS learning framework for modeling the formation of equivalence ...

    • Estimating tukey depth using incremental quantile estimators 

      Hammer, Hugo Lewi; Yazidi, Anis; Rue, Håvard (Pattern Recognition;Volume 122, February 2022, 108339, Peer reviewed; Journal article, 2022)
      Measures of distance or how data points are positioned relative to each other are fundamental in pattern recognition. The concept of depth measures how deep an arbitrary point is positioned in a dataset, and is an interesting ...

    • Evading a Machine Learning-based Intrusion Detection System through Adversarial Perturbations 

      Fladby, Torgeir; Haugerud, Hårek; Nichele, Stefano; Begnum, Kyrre; Yazidi, Anis (RACS: Research in Applied Computation Symposium; RACS '20: International Conference on Research in Adaptive and Convergent Systems, Chapter; Peer reviewed; Conference proceeding, 2020-10)
      Machine-learning based Intrusion Detection and Prevention Systems provide significant value to organizations because they can efficiently detect previously unseen variations of known threats, new threats related to known ...

    • EvoDynamic: A Framework for the Evolution of Generally Represented Dynamical Systems and Its Application to Criticality 

      Pontes-Filho, Sidney; Lind, Pedro; Yazidi, Anis; Zhang, Jianhua; Hammer, Hugo Lewi; Mello, Gustavo; Sandvig, Ioanna; Tufte, Gunnar; Nichele, Stefano (Lecture Notes in Computer Science;Volume 12104, Conference object, 2020-04-09)
      Dynamical systems possess a computational capacity that may be exploited in a reservoir computing paradigm. This paper presents a general representation of dynamical systems which is based on matrix multiplication. That ...

    • Exploring multilingual and contextual properties in word representations from BERT 

      Aaby, Pernille (ACIT;2022, Master thesis, 2022)
      Nowadays, contextual language models can solve a wide range of language tasks such as text classification, question answering and machine translation. These tasks often require the model to have knowledge about general ...

    • Exploring Multilingual Word Embedding Alignments in BERT Models: A Case Study of English and Norwegian 

      Aaby, Pernille; Biermann, Daniel; Yazidi, Anis; Borges Moreno e Mello, Gustavo; Palumbo, Fabrizio (Lecture Notes in Computer Science;, Chapter; Peer reviewed; Conference object; Journal article, 2023)
      Contextual language models, such as transformers, can solve a wide range of language tasks ranging from text classification to question answering and machine translation. Like many deep learning models, the performance ...

    • Exploring Multilingual Word Embedding Alignments in BERT Models: A Case Study of English and Norwegian 

      Aaby, Pernille; Biermann, Daniel; Yazidi, Anis; Borges Moreno e Mello, Gustavo; Palumbo, Fabrizio (Chapter; Peer reviewed; Conference object; Journal article, 2023)
      Contextual language models, such as transformers, can solve a wide range of language tasks ranging from text classification to question answering and machine translation. Like many deep learning models, the performance ...

    • Exploring the Value of GANs for Synthetic Tabular Data Generation in Healthcare with a Focus on Data Quality, Augmentation, and Privacy 

      Pedersen, Maria Elinor (Master thesis, 2023)
      Artificial Intelligence has demonstrated immense potential in healthcare-related applications, paving the way for advancements in diagnosis, treatment, and patient care. However, data protection laws and regulations present ...

    • Exploring thehHyperparameter space of U-Net using genetic algorithms 

      Holland, Jon-Olav (ACIT;2022, Master thesis, 2022)
      U-Net based architecture has become the de-facto standard approach for medical image segmentation in recent years. Many researchers have used the original U-Net as a skeleton for suggesting more advanced models such as ...