CatBoost for big data: an interdisciplinary review

JT Hancock, TM Khoshgoftaar - Journal of big data, 2020 - Springer
Abstract Gradient Boosted Decision Trees (GBDT's) are a powerful tool for classification and
regression tasks in Big Data. Researchers should be familiar with the strengths and …

Data-centric artificial intelligence: A survey

D Zha, ZP Bhat, KH Lai, F Yang, Z Jiang… - ACM Computing …, 2025 - dl.acm.org
Artificial Intelligence (AI) is making a profound impact in almost every domain. A vital enabler
of its great success is the availability of abundant and high-quality data for building machine …

Datacomp: In search of the next generation of multimodal datasets

SY Gadre, G Ilharco, A Fang… - Advances in …, 2024 - proceedings.neurips.cc
Multimodal datasets are a critical component in recent breakthroughs such as CLIP, Stable
Diffusion and GPT-4, yet their design does not receive the same research attention as model …

Error metrics and performance fitness indicators for artificial intelligence and machine learning in engineering and sciences

MZ Naser, AH Alavi - Architecture, Structures and Construction, 2023 - Springer
Artificial intelligence (AI) and Machine learning (ML) train machines to achieve a high level
of cognition and perform human-like analysis. Both AI and ML seemingly fit into our daily …

[HTML][HTML] Forecasting: theory and practice

F Petropoulos, D Apiletti, V Assimakopoulos… - International Journal of …, 2022 - Elsevier
Forecasting has always been at the forefront of decision making and planning. The
uncertainty that surrounds the future is both exciting and challenging, with individuals and …

[HTML][HTML] Renewable energy management in smart grids by using big data analytics and machine learning

N Mostafa, HSM Ramadan, O Elfarouk - Machine Learning with …, 2022 - Elsevier
The application of big data in the energy sector is considered as one of the main elements of
Energy Internet. Crucial and promising challenges exist especially with the integration of …

A survey on distributed machine learning

J Verbraeken, M Wolting, J Katzy… - Acm computing surveys …, 2020 - dl.acm.org
The demand for artificial intelligence has grown significantly over the past decade, and this
growth has been fueled by advances in machine learning techniques and the ability to …

A comprehensive survey of anomaly detection techniques for high dimensional big data

S Thudumu, P Branch, J **, J Singh - Journal of Big Data, 2020 - Springer
Anomaly detection in high dimensional data is becoming a fundamental research problem
that has various applications in the real world. However, many existing anomaly detection …

Artificial intelligence, cyber-threats and Industry 4.0: Challenges and opportunities

A Bécue, I Praça, J Gama - Artificial Intelligence Review, 2021 - Springer
This survey paper discusses opportunities and threats of using artificial intelligence (AI)
technology in the manufacturing sector with consideration for offensive and defensive uses …

A survey on IoT intrusion detection: Federated learning, game theory, social psychology, and explainable AI as future directions

S Arisdakessian, OA Wahab, A Mourad… - IEEE Internet of …, 2022 - ieeexplore.ieee.org
In the past several years, the world has witnessed an acute surge in the production and
usage of smart devices which are referred to as the Internet of Things (IoT). These devices …