Efficient Automation of Neural Network Design: A Survey on Differentiable Neural Architecture Search
In the past few years, Differentiable Neural Architecture Search (DNAS) rapidly imposed itself as the trending approach to automate the discovery of deep neural network architectures. This rise is mainly due to the popularity of DARTS (Differentiable ...
Synthetic Data for Deep Learning in Computer Vision & Medical Imaging: A Means to Reduce Data Bias
Deep-learning (DL) performs well in computer-vision and medical-imaging automated decision-making applications. A bottleneck of DL stems from the large amount of labelled data required to train accurate models that generalise well. Data scarcity and ...
A Review of Symbolic, Subsymbolic and Hybrid Methods for Sequential Decision Making
In the field of Sequential Decision Making (SDM), two paradigms have historically vied for supremacy: Automated Planning (AP) and Reinforcement Learning (RL). In the spirit of reconciliation, this article reviews AP, RL and hybrid methods (e.g., novel ...
A Survey of Multi-modal Knowledge Graphs: Technologies and Trends
In recent years, Knowledge Graphs (KGs) have played a crucial role in the development of advanced knowledge-intensive applications, such as recommender systems and semantic search. However, the human sensory system is inherently multi-modal, as objects ...
A Review of Explainable Fashion Compatibility Modeling Methods
The paper reviews methods used in the fashion compatibility recommendation domain. We select methods based on reproducibility, explainability, and novelty aspects and then organize them chronologically and thematically. We presented general ...
Survey on Redundancy Based-Fault tolerance methods for Processors and Hardware accelerators - Trends in Quantum Computing, Heterogeneous Systems and Reliability
Rapid progress in CMOS technology since the late 1990s has increased the vulnerability of processors toward faults. Subsequently, the focus of computer architects has shifted toward designing fault-tolerance methods for processor architectures. ...
A Review of Olfactory Display Designs for Virtual Reality Environments
The field of Virtual Reality continues to evolve to provide an ever-greater sense of immersion to the user. However, VR experiences are still primarily constrained through the human senses of vision and audition, with some interest in haptic (mainly ...
Self-tuning Database Systems: A Systematic Literature Review of Automatic Database Schema Design and Tuning
Self-tuning is a feature of autonomic databases that includes the problem of automatic schema design. It aims at providing an optimized schema that increases the overall database performance. While in relational databases automatic schema design focuses ...
A Survey on Malware Detection with Graph Representation Learning
Malware detection has become a major concern due to the increasing number and complexity of malware. Traditional detection methods based on signatures and heuristics are used for malware detection, but unfortunately, they suffer from poor generalization ...
Human Image Generation: A Comprehensive Survey
Image and video synthesis has become a blooming topic in computer vision and machine learning communities along with the developments of deep generative models, due to its great academic and application value. Many researchers have been devoted to ...
Machine Learning with Confidential Computing: A Systematization of Knowledge
Privacy and security challenges in Machine Learning (ML) have become increasingly severe, along with ML’s pervasive development and the recent demonstration of large attack surfaces. As a mature system-oriented approach, Confidential Computing has been ...
Lexical Semantic Change through Large Language Models: a Survey
Lexical Semantic Change (LSC) is the task of identifying, interpreting, and assessing the possible change over time in the meanings of a target word. Traditionally, LSC has been addressed by linguists and social scientists through manual and time-...
Creativity and Machine Learning: A Survey
There is a growing interest in the area of machine learning and creativity. This survey presents an overview of the history and the state of the art of computational creativity theories, key machine learning techniques (including generative deep learning),...
“Are you feeling sick?” – A systematic literature review of cybersickness in virtual reality
Cybersickness (CS), also known as visually induced motion sickness (VIMS), is a condition that can affect individuals when they interact with virtual reality (VR) technology. This condition is characterized by symptoms such as nausea, dizziness, headaches,...
Databases in Edge and Fog Environments: A Survey
While a significant number of databases are deployed in cloud environments, pushing part or all data storage and querying planes closer to their sources (i.e., to the edge) can provide advantages in latency, connectivity, privacy, energy, and scalability. ...
Secure UAV (Drone) and the Great Promise of AI
UAVs have found their applications in numerous applications from recreational activities to business in addition to military and strategic fields. However, research on UAVs is not going on as quickly as the technology. Especially, when it comes to the ...
AI-Based Affective Music Generation Systems: A Review of Methods and Challenges
Music is a powerful medium for altering the emotional state of the listener. In recent years, with significant advancements in computing capabilities, artificial intelligence-based (AI-based) approaches have become popular for creating affective music ...
Research Progress of EEG-Based Emotion Recognition: A Survey
Emotion recognition based on electroencephalography (EEG) signals has emerged as a prominent research field, facilitating objective evaluation of diseases like depression and motion detection for heathy people. Starting from the basic concepts of temporal-...
Macro Ethics Principles for Responsible AI Systems: Taxonomy and Directions
Responsible AI must be able to make or support decisions that consider human values and can be justified by human morals. Accommodating values and morals in responsible decision making is supported by adopting a perspective of macro ethics, which views ...
An Introduction to the Compute Express Link (CXL) Interconnect
The Compute Express Link (CXL) is an open industry-standard interconnect between processors and devices such as accelerators, memory buffers, smart network interfaces, persistent memory, and solid-state drives. CXL offers coherency and memory semantics ...