159 citations · 194 across the 29 of their papers we have counts for
29 papers
Cross-Domain Industrial Fault Detection by Causal Mechanism Monitoring
Dhiraj Neupane, Mohamed Reda Bouadjenek, Richard Dazeley +1
Unsupervised fault detection in industrial systems is dominated by reconstruction based methods that monitor individual sensor marginal distributions. This misses coupling faults,…
Label-free Industrial Fault Detection via Adversarial Inverse Reinforcement Learning: A System for Run-to-Failure Prognostics
Dhiraj Neupane, Mohamed Reda Bouadjenek, Richard Dazeley +1
Machinery fault detection (MFD) remains heavily reliant on supervised learning, which struggles with the scarcity of fault labels in real-world settings. While reinforcement learni…
Memory Merge DQN: Sensitivity Weighted Target Updates for Stable Value Learning
Adrian Ly, Richard Dazeley, Peter Vamplew +2
Deep Q-networks use target networks to stabilise bootstrapped value learning, but the standard hard copy update also introduces a tradeoff. Holding the target network fixed, improv…
Learning Rewards, Not Labels: Adversarial Inverse Reinforcement Learning for Machinery Fault Detection
Dhiraj Neupane, Richard Dazeley, Mohamed Reda Bouadjenek +1
Reinforcement learning (RL) offers significant promise for machinery fault detection (MFD). However, most existing RL-based MFD approaches do not fully exploit RL's sequential deci…
IVGAE: Handling Incomplete Heterogeneous Data with a Variational Graph Autoencoder
Youran Zhou, Mohamed Reda Bouadjenek, Sunil Aryal%
Handling missing data remains a fundamental challenge in real-world tabular datasets, especially when data are heterogeneous with both numerical and categorical features. Existing…
MissHDD: Hybrid Deterministic Diffusion for Hetrogeneous Incomplete Data Imputation
Youran Zhou, Mohamed Reda Bouadjenek, Sunil Aryal
Incomplete data are common in real-world tabular applications, where numerical, categorical, and discrete attributes coexist within a single dataset. This heterogeneous structure p…
MissMecha: An All-in-One Python Package for Studying Missing Data Mechanisms
Youran Zhou, Mohamed Reda Bouadjenek, Sunil Aryal
Incomplete data is a persistent challenge in real-world datasets, often governed by complex and unobservable missing mechanisms. Simulating missingness has become a standard approa…
MissDDIM: Deterministic and Efficient Conditional Diffusion for Tabular Data Imputation
Youran Zhou, Mohamed Reda Bouadjenek, Sunil Aryal
Diffusion models have recently emerged as powerful tools for missing data imputation by modeling the joint distribution of observed and unobserved variables. However, existing meth…
Handling Out-of-Distribution Data: A Survey
Lakpa Tamang, Mohamed Reda Bouadjenek, Richard Dazeley +1
In the field of Machine Learning (ML) and data-driven applications, one of the significant challenge is the change in data distribution between the training and deployment stages,…
Far From Sight, Far From Mind: Inverse Distance Weighting for Graph Federated Recommendation
Aymen Rayane Khouas, Mohamed Reda Bouadjenek, Hakim Hacid +1
Graph federated recommendation systems offer a privacy-preserving alternative to traditional centralized recommendation architectures, which often raise concerns about data securit…
Multi-Focus Temporal Shifting for Precise Event Spotting in Sports Videos
Hao Xu, Xinyu Wei, Sam Wells +1
Precise Event Spotting (PES) in sports videos requires frame-level recognition of fine-grained actions from single-camera footage. Existing PES models typically incorporate lightwe…
Bias vs Bias -- Dawn of Justice: A Fair Fight in Recommendation Systems
Tahsin Alamgir Kheya, Mohamed Reda Bouadjenek, Sunil Aryal
Recommendation systems play a crucial role in our daily lives by impacting user experience across various domains, including e-commerce, job advertisements, entertainment, etc. Giv…
A Comprehensive Analysis of Large Language Model Outputs: Similarity, Diversity, and Bias
Brandon Smith, Mohamed Reda Bouadjenek, Tahsin Alamgir Kheya +2
Large Language Models (LLMs) represent a major step toward artificial general intelligence, significantly advancing our ability to interact with technology. While LLMs perform well…
Rolling Ball Optimizer: Learning by ironing out loss landscape wrinkles
Mohammed Djameleddine Belgoumri, Mohamed Reda Bouadjenek, Hakim Hacid +2
Training large neural networks (NNs) requires optimizing high-dimensional data-dependent loss functions. The optimization landscape of these functions is often highly complex and t…
Deep Learning for Sports Video Event Detection: Tasks, Datasets, Methods, and Challenges
Hao Xu, Arbind Agrahari Baniya, Sam Well +3
Video event detection has become a cornerstone of modern sports analytics, powering automated performance evaluation, content generation, and tactical decision-making. Recent advan…
SVLA: A Unified Speech-Vision-Language Assistant with Multimodal Reasoning and Speech Generation
Ngoc Dung Huynh, Mohamed Reda Bouadjenek, Imran Razzak +2
Large vision and language models show strong performance in tasks like image captioning, visual question answering, and retrieval. However, challenges remain in integrating speech,…
Developing robust methods to handle missing data in real-world applications effectively
Youran Zhou, Mohamed Reda Bouadjenek, Sunil Aryal
Missing data is a pervasive challenge spanning diverse data types, including tabular, sensor data, time-series, images and so on. Its origins are multifaceted, resulting in various…
Visual question answering: from early developments to recent advances -- a survey
Ngoc Dung Huynh, Mohamed Reda Bouadjenek, Sunil Aryal +2
Visual Question Answering (VQA) is an evolving research field aimed at enabling machines to answer questions about visual content by integrating image and language processing techn…
HI-PMK: A Data-Dependent Kernel for Incomplete Heterogeneous Data Representation
Youran Zhou, Mohamed Reda Bouadjenek, Jonathan Wells +1
Handling incomplete and heterogeneous data remains a central challenge in real-world machine learning, where missing values may follow complex mechanisms (MCAR, MAR, MNAR) and feat…
SimpsonsVQA: Enhancing Inquiry-Based Learning with a Tailored Dataset
Ngoc Dung Huynh, Mohamed Reda Bouadjenek, Sunil Aryal +2
Visual Question Answering (VQA) has emerged as a promising area of research to develop AI-based systems for enabling interactive and immersive learning. Numerous VQA datasets have…
Margin-bounded Confidence Scores for Out-of-Distribution Detection
Lakpa D. Tamang, Mohamed Reda Bouadjenek, Richard Dazeley +1
In many critical Machine Learning applications, such as autonomous driving and medical image diagnosis, the detection of out-of-distribution (OOD) samples is as crucial as accurate…
Data Quality in Edge Machine Learning: A State-of-the-Art Survey
Mohammed Djameleddine Belgoumri, Mohamed Reda Bouadjenek, Sunil Aryal +1
Data-driven Artificial Intelligence (AI) systems trained using Machine Learning (ML) are shaping an ever-increasing (in size and importance) portion of our lives, including, but no…
Data-driven Machinery Fault Diagnosis: A Comprehensive Review
Dhiraj Neupane, Mohamed Reda Bouadjenek, Richard Dazeley +1
In this era of advanced manufacturing, it's now more crucial than ever to diagnose machine faults as early as possible to guarantee their safe and efficient operation. With the mas…
Review for Handling Missing Data with special missing mechanism
Youran Zhou, Sunil Aryal, Mohamed Reda Bouadjenek
Missing data poses a significant challenge in data science, affecting decision-making processes and outcomes. Understanding what missing data is, how it occurs, and why it is cruci…