AI-big data analytics for building automation and management systems: a survey, actual challenges and future perspectives

Y Himeur, M Elnour, F Fadli, N Meskin, I Petri… - Artificial Intelligence …, 2023 - Springer
In theory, building automation and management systems (BAMSs) can provide all the
components and functionalities required for analyzing and operating buildings. However, in …

Wisefuse: Workload characterization and dag transformation for serverless workflows

A Mahgoub, EB Yi, K Shankar, E Minocha… - Proceedings of the …, 2022 - dl.acm.org
We characterize production workloads of serverless DAGs at a major cloud provider. Our
analysis highlights two major factors that limit performance:(a) lack of efficient …

FastSVD-ML–ROM: A reduced-order modeling framework based on machine learning for real-time applications

GI Drakoulas, TV Gortsas, GC Bourantas… - Computer Methods in …, 2023 - Elsevier
Digital twins have emerged as a key technology for optimizing the performance of
engineering products and systems. High-fidelity numerical simulations constitute the …

Collaborative filtering integrated fine-grained sentiment for hybrid recommender system

R Alatrash, R Priyadarshini, H Ezaldeen - The Journal of Supercomputing, 2024 - Springer
Develo** online educational platforms necessitates the incorporation of new intelligent
procedures in order to improve long-term student experience. Presently, e-learning …

Single-pass top-N subgraph centrality of graphs via subspace projections

V Kalantzis, G Kollias, S Ubaru, N Abe… - Journal of Complex …, 2025 - academic.oup.com
Subgraph centrality is a widely used centrality measure to rank the the importance of
vertices in graphs. Due to the cubic cost of matrix diagonalization, subgraph centrality scores …

Matrix resolvent eigenembeddings for dynamic graphs

V Kalantzis, PA Traganitis - ICASSP 2023-2023 IEEE …, 2023 - ieeexplore.ieee.org
Eigenvector embeddings have been widely used to study graph properties in signal
processing, mining, and learning tasks. However, if a graph is changing dynamically, these …

Rayleigh-Ritz Based Updates of the Multilinear Singular Value Decomposition

V Kalantzis, PA Traganitis - 2023 57th Asilomar Conference on …, 2023 - ieeexplore.ieee.org
Multilinear singular value decomposition (MLSVD), also known as Higher-order SVD
(HOSVD), is a popular method for approximating a tensor of order≥ 3 via a smaller core …

Counting Triangles of Graphs via Matrix Partitioning

G Kollias, V Kalantzis, L Horesh… - 2024 IEEE 34th …, 2024 - ieeexplore.ieee.org
Counting the number of triangles is an important task in the computation of several network-
related metrics such as transitivity ratio, link recommendation, near-clique subgraph …

Fast Updating Truncated SVD for Representation Learning with Sparse Matrices

H Deng, Y Yang, J Li, C Chen, W Jiang… - arxiv preprint arxiv …, 2024 - arxiv.org
Updating a truncated Singular Value Decomposition (SVD) is crucial in representation
learning, especially when dealing with large-scale data matrices that continuously evolve in …

Dynamic Collaborative Filtering for Matrix-and Tensor-based Recommender Systems

A Saiapin, I Oseledets, E Frolov - arxiv preprint arxiv:2312.10064, 2023 - arxiv.org
In production applications of recommender systems, a continuous data flow is employed to
update models in real-time. Many recommender models often require complete retraining to …