Deep Reinforcement Learning for Resource Constrained HLS Scheduling by Makhoul, Rim

“…In this work, we present a resource constrained scheduling approach that minimizes latency and subject to resource constraints using a deep Q learning algorithm. …”
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Benchmarking Concept Drift Detectors for Online Machine Learning by Mahgoub, Mahmoud

“…Upon drift detection, the classifica tion algorithm may reset its model or concurrently grow a new learning model. …”
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Inertial Navigation system of In-pipe Inspection Robot by Al-Masri, Wasim

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DAP: A dataset-agnostic predictor of neural network performance by Sui Paul Ang (18460605)

“…This task often must be repeated many times, especially when developing a new deep learning algorithm or performing a neural architecture search. …”

Positive Unlabelled Learning to Recognize Dishes as Named Entity by TAREK, AIMAN

“…This research has the potential to be extended to other topics other than food and dish names, also it acts as a framework and algorithm independent.…”
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Multi-Agent Learning of Strategies in Abstract Argumentation Mechanisms by Nemer, Rama

“…As for the effect of the learning algorithm on the choice of strategy, the results confirm that WPL is biased toward mixed strategies while GIGA is faster in convergence to pure strategy Nash equilibria. …”
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Reinforcement Learning-Based School Energy Management System by Yassine Chemingui (18891757)

“…In this work, a Deep Reinforcement Learning agent is proposed for controlling and optimizing a school building’s energy consumption. …”

Finetuning Analytics Information Systems for a Better Understanding of Users: Evidence of Personification Bias on Multiple Digital Channels by Bernard J. Jansen (7434779)

“…<p dir="ltr">Although the effect of hyperparameters on algorithmic outputs is well known in machine learning, the effects of hyperparameters on information systems that produce user or customer segments are relatively unexplored. …”

Modulation With Metaheuristic Approach for Cascaded-MPUC49 Asymmetrical Inverter With Boosted Output by Kaif Ahmed Lodi (16855518)

Machine Learning-Based Approach for EV Charging Behavior by Shahriar, Sakib

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LDSVM: Leukemia Cancer Classification Using Machine Learning by Abdul Karim (417009)

“…However, they are not highly effective in improving results and are frequently employed by doctors for cancer diagnosis. This study proposes a novel method using machine learning algorithms based on microarrays of leukemia GSE9476 cells. …”

Malicious URL and Intrusion Detection using Machine Learning by Hamza, Amr

“…Therefore, addressing the growing threat of cyberattacks and providing automated solutions became a necessity. The purpose of this paper is to use machine learning (ML) techniques for malicious websites detection and classification, and intrusion detection. …”
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Cyberbullying Detection in Arabic Text using Deep Learning by ALBAYARI, REEM RAMADAN SA’ID

“…In this study, I conduct a performance evaluation and comparison for various DL algorithms (LSTM, GRU, LSTM-ATT, CNN-BLSTM, CNN-LSTM, CNN-BILSTM-LSTM, and LSTM-TCN) on different datasets of Arabic cyberbullying to obtain more precise and dependable findings. …”
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Using machine learning to support students’ academic decisions by ALLAH, AISHA QASIM GHAZAL FATEH

“…This approach uses other students’ grades to make a prediction. This research tests and compares the performance of Decision Trees, Random Forests, Gradient-Boosted trees, and Deep Learning machine learning regression algorithms to predict student GPA. …”
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DRL-Based IRS-Assisted Secure Hybrid Visible Light and mmWave Communications by Danya A. Saifaldeen (19498705)

“…To address this complexity optimally, we propose a deep reinforcement learning (DRL) approach based on the deep deterministic policy gradient (DDPG) technique. …”

Dynamic performance evaluation and machine learning-assisted optimization of a solar-driven system integrated with PCM-based thermal energy storage: A case study approach by Haitham Osman (11737057)

“…Sensitivity and parametric analyses identify key performance parameters. A comprehensive techno-economic analysis is conducted, supported by a machine learning-assisted optimization framework that combines artificial neural networks with genetic algorithms. …”

Multi Agent Reinforcement Learning Approach for Autonomous Fleet Management by Alhusin, Mohammed Omer Alamin

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The effects of data balancing approaches: A case study by Paul Mooijman (4453189)

“…<p dir="ltr">Imbalanced datasets affect the performance of machine learning algorithms adversely. To cope with this problem, several resampling methods have been developed recently. …”

Hybrid Deep Learning-based Models for Crop Yield Prediction by Alexandros Oikonomidis (12050497)

“…In this study, we developed deep learning-based models to evaluate how the underlying algorithms perform with respect to different performance criteria. …”

Single channel speech denoising by DDPG reinforcement learning agent by Sania Gul (18272227)

“…In this paper, a novel SD algorithm is presented based on the deep deterministic policy gradient (DDPG) agent; an off-policy reinforcement learning (RL) agent with a continuous action space. …”