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Found 15 papers, 2 papers with code
Manipulating Recommender Systems: A Survey of Poisoning Attacks and Countermeasures
This survey aims to fill this gap by primarily focusing on poisoning attacks and their countermeasures.
Fine-Tuning Llama 2 Large Language Models for Detecting Online Sexual Predatory Chats and Abusive Texts
Detecting online sexual predatory behaviours and abusive language on social media platforms has become a critical area of research due to the growing concerns about online safety, especially for vulnerable populations such as children and adolescents.
Detecting Rumours with Latency Guarantees using Massive Streaming Data
Today's social networks continuously generate massive streams of data, which provide a valuable starting point for the detection of rumours as soon as they start to propagate.
Artificial Intelligence for the Metaverse: A Survey
Many virtual environments with thousands of services and applications, from social networks to virtual gaming worlds, have been developed with immersive experience and digital transformation, but most are incoherent instead of being integrated into a platform.
A War Beyond Deepfake: Benchmarking Facial Counterfeits and Countermeasures
In recent years, visual forgery has reached a level of sophistication that humans cannot identify fraud, which poses a significant threat to information security.
Deep Learning Methods for Credit Card Fraud Detection
This paper presents a thorough study of deep learning methods for the credit card fraud detection problem and compare their performance with various machine learning algorithms on three different financial datasets.
Artificial Intelligence in the Battle against Coronavirus (COVID-19): A Survey and Future Research Directions
Artificial intelligence (AI) has been applied widely in our daily lives in a variety of ways with numerous success stories.
Deep Auto-Encoders with Sequential Learning for Multimodal Dimensional Emotion Recognition
Multimodal dimensional emotion recognition has drawn a great attention from the affective computing community and numerous schemes have been extensively investigated, making a significant progress in this area.
Review, Analysis and Design of a Comprehensive Deep Reinforcement Learning Framework
However, development of a deep RL-based system is challenging because of various issues such as the selection of a suitable deep RL algorithm, its network configuration, training time, training methods, and so on.
A Visual Communication Map for Multi-Agent Deep Reinforcement Learning
In this paper, we have proposed a more scalable approach that not only deals with a great number of agents but also enables collaboration between dissimilar functional agents and compatibly combined with any deep reinforcement learning methods.
Deep Learning for Deepfakes Creation and Detection: A Survey
By reviewing the background of deepfakes and state-of-the-art deepfake detection methods, this study provides a comprehensive overview of deepfake techniques and facilitates the development of new and more robust methods to deal with the increasingly challenging deepfakes.
Deep Reinforcement Learning for Cyber Security
The scale of Internet-connected systems has increased considerably, and these systems are being exposed to cyber attacks more than ever.
A New Tensioning Method using Deep Reinforcement Learning for Surgical Pattern Cutting
Surgeons normally need surgical scissors and tissue grippers to cut through a deformable surgical tissue.
Deep Reinforcement Learning for Multi-Agent Systems: A Review of Challenges, Solutions and Applications
Reinforcement learning (RL) algorithms have been around for decades and employed to solve various sequential decision-making problems.
A Multi-Objective Deep Reinforcement Learning Framework
This paper introduces a new scalable multi-objective deep reinforcement learning (MODRL) framework based on deep Q-networks.
Multi-Objective Reinforcement Learning
reinforcement-learning
