Blar i AURA på forfatter "Yazidi, Anis"
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Dynamic Ordering of Firewall Rules Using a Novel Swapping Window-based Paradigm
Mohan, Ratish; Yazidi, Anis; Feng, Boning; Oommen, John (Chapter, 2016) -
Expert Q-learning: Deep Reinforcement Learning with Coarse State Values from Offline Expert Examples
Meng, Li; Yazidi, Anis; Goodwin, Morten; Engelstad, Paal (Peer reviewed; Journal article, 2022)In this article, we propose a novel algorithm for deep reinforcement learning named Expert Q-learning. Expert Q-learning is inspired by Dueling Q-learning and aims to incorporate semi-supervised learning into reinforcement ... -
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, 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 ... -
The Hierarchical Continuous Pursuit Learning Automation : A Novel Scheme for Environments With Large Numbers of Actions
Yazidi, Anis; Zhang, Xuan; Lei, Jiao; Oommen, John (Journal article; Peer reviewed, 2019) -
The Hierarchical Discrete Learning Automaton Suitable for Environments with Many Actions and High Accuracy Requirements
Omslandseter, Rebekka Olsson; Jiao, Lei; Zhang, Xuan; Yazidi, Anis; Oommen, John (Peer reviewed; Journal article, 2022)Since its early beginning, the paradigm of Learning Automata (LA), has attracted much interest. Over the last decades, new concepts and various improvements have been introduced to increase the LA’s speed and accuracy, ... -
The Hierarchical Discrete Pursuit Learning Automaton: A Novel Scheme With Fast Convergence and Epsilon-Optimality
Omslandseter, Rebekka Olsson; Jiao, Lei; Zhang, Xuan; Yazidi, Anis; Oommen, John (Peer reviewed; Journal article, 2022)Since the early 1960s, the paradigm of learning automata (LA) has experienced abundant interest. Arguably, it has also served as the foundation for the phenomenon and field of reinforcement learning (RL). Over the decades, ... -
Higher-Fidelity Frugal and Accurate Quantile Estimation Using a Novel Incremental Discretized Paradigm
Yazidi, Anis; Hammer, Hugo Lewi; Oommen, John (Journal article; Peer reviewed, 2018) -
Identifying unreliable sensors without a knowledge of the ground truth in deceptive environments
Yazidi, Anis; Oommen, John; Goodwin, Morten (Journal article; Peer reviewed, 2017)This paper deals with the extremely fascinating area of “fusing” the outputs of sensors without any knowledge of the ground truth. In an earlier paper, the present authors had recently pioneered a solution, by mapping ... -
Improving Classification of Tweets Using Linguistic Information from a Large External Corpus
Hammer, Hugo Lewi; Yazidi, Anis; Bai, Aleksander; Engelstad, Paal E. (Chapter, 2016) -
Improving the Diversity of Bootstrapped DQN by Replacing Priors With Noise
Meng, Li; Goodwin, Morten; Yazidi, Anis; Engelstad, Paal (Peer reviewed; Journal article, 2022)Q-learning is one of the most well-known Reinforcement Learning algorithms. There have been tremendous efforts to develop this algorithm using neural networks. Bootstrapped Deep Q-Learning Network is amongst them. It ... -
Intelligent Learning Automata-based Strategies Applied to Personalized Service Provisioning in Pervasive Environments
Yazidi, Anis (Doctoral dissertations at the University of Agder;43, Doctoral thesis, 2011) -
Intelligent Learning Automata-based Strategies Applied to Personalized Service Provisioning in Pervasive Environments
Yazidi, Anis (Doctoral dissertations at the University of Agder;43, Doctoral thesis, 2011) -
A Learning Automata Based Solution to Service Selection in Stochastic Environments
Yazidi, Anis; Granmo, Ole-Christoffer; Oommen, B. John (Chapter; Peer reviewed, 2010)With the abundance of services available in today’s world, identifying those of high quality is becoming increasingly difficult. Reputation systems can offer generic recommendations by aggregating user provided opinions ... -
Learning Automaton Based On-Line Discovery and Tracking of Spatio-temporal Event Patterns
Yazidi, Anis; Granmo, Ole-Christoffer; Lin, Min; Wen, Xifeng; Oommen, B. John; Gerdes, Martin; Reichert, Frank (Lecture Notes in Computer Science; no. 6230, Journal article; Peer reviewed, 2010)Discovering and tracking of spatio-temporal patterns in noisy sequences of events is a difficult task that has become increasingly pertinent due to recent advances in ubiquitous computing, such as community-based social ... -
A new tool for the modeling of AI and machine learning applications: Random walk-jump processes
Yazidi, Anis; Granmo, Ole-Christoffer; Oommen, B. John (Lecture notes in computer science;6678, Chapter; Peer reviewed, 2011)There are numerous applications in Artificial Intelligence (AI) and Machine Learning (ML) where the criteria for decisions are based on testing procedures. The most common tools used in such random phenomena involve Random ... -
On achieving intelligent traffic-aware consolidation of virtual machines in a data center using Learning Automata
Jobava, Akaki; Yazidi, Anis; Oommen, John; Begnum, Kyrre (Journal article; Peer reviewed, 2017)Unlike the computational mechanisms of the past many decades, that involved individual (extremely powerful) computers or clusters of machines, cloud computing (CC) is becoming increasingly pertinent and popular. Computing ... -
On Distinguishing between Reliable and Unreliable Sensors Without a Knowledge of the Ground Truth
Yazidi, Anis; Oommen, John; Goodwin, Morten (Chapter; Peer reviewed, 2015) -
On optimizing firewall performance in dynamic networks by invoking a novel swapping window-based paradigm
Mohan, Ratish; Yazidi, Anis; Feng, Boning; Oommen, John (Journal article; Peer reviewed, 2018) -
On Solving the Problem of Identifying Unreliable Sensors Without a Knowledge of the Ground Truth: The Case of Stochastic Environments
Yazidi, Anis; Oommen, John; Goodwin, Morten (Journal article; Peer reviewed, 2016)The purpose of this paper is to propose a solution to an extremely pertinent problem, namely, that of identifying unreliable sensors (in a domain of reliable and unreliable ones) without any knowledge of the ground truth. ... -
On the analysis of a new Markov chain which has applications in AI and machine learning
Yazidi, Anis; Granmo, Ole-Christoffer; Oommen, B. John (Chapter; Peer reviewed, 2011)In this paper, we consider the analysis of a fascinating Random Walk (RW) that contains interleaving random steps and random "jumps". The characterizing aspect of such a chain is that every step is paired with its counterpart ...