Challenges in deploying machine learning: a survey of case studies
In recent years, machine learning has transitioned from a field of academic research interest
to a field capable of solving real-world business problems. However, the deployment of …
to a field capable of solving real-world business problems. However, the deployment of …
The use of generative adversarial networks to alleviate class imbalance in tabular data: a survey
R Sauber-Cole, TM Khoshgoftaar - Journal of Big Data, 2022 - Springer
The existence of class imbalance in a dataset can greatly bias the classifier towards majority
classification. This discrepancy can pose a serious problem for deep learning models, which …
classification. This discrepancy can pose a serious problem for deep learning models, which …
The role of machine learning in cybersecurity
Machine Learning (ML) represents a pivotal technology for current and future information
systems, and many domains already leverage the capabilities of ML. However, deployment …
systems, and many domains already leverage the capabilities of ML. However, deployment …
Software engineering for AI-based systems: a survey
AI-based systems are software systems with functionalities enabled by at least one AI
component (eg, for image-, speech-recognition, and autonomous driving). AI-based systems …
component (eg, for image-, speech-recognition, and autonomous driving). AI-based systems …
EEGDnet: Fusing non-local and local self-similarity for EEG signal denoising with transformer
Electroencephalogram (EEG) has shown a useful approach to produce a brain–computer
interface (BCI). One-dimensional (1-D) EEG signal is yet easily disturbed by certain artifacts …
interface (BCI). One-dimensional (1-D) EEG signal is yet easily disturbed by certain artifacts …
Improving multi-scenario learning to rank in e-commerce by exploiting task relationships in the label space
Traditional Learning to Rank (LTR) models in E-commerce are usually trained on logged
data from a single domain. However, data may come from multiple domains, such as …
data from a single domain. However, data may come from multiple domains, such as …
[HTML][HTML] Monitoring machine learning models: a categorization of challenges and methods
T Schröder, M Schulz - Data Science and Management, 2022 - Elsevier
The importance of software based on machine learning is growing rapidly, but the potential
of prototypes may not be realized in operation. This study identified six categories of …
of prototypes may not be realized in operation. This study identified six categories of …
Demand forecasting model using hotel clustering findings for hospitality industry
Tourism has become a growing industry day by day with the develo** economic
conditions and the increasing communication and social interaction ability of the people …
conditions and the increasing communication and social interaction ability of the people …
Machine learning-based ABA treatment recommendation and personalization for autism spectrum disorder: an exploratory study
Autism spectrum is a brain development condition that impairs an individual's capacity to
communicate socially and manifests through strict routines and obsessive–compulsive …
communicate socially and manifests through strict routines and obsessive–compulsive …
Corporate relative valuation using heterogeneous multi-modal graph neural network
Corporate relative valuation (CRV) refers to the process of comparing a company's value
from company products, core staff and other related information, so that we can assess the …
from company products, core staff and other related information, so that we can assess the …