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AI-big data analytics for building automation and management systems: a survey, actual challenges and future perspectives
In theory, building automation and management systems (BAMSs) can provide all the
components and functionalities required for analyzing and operating buildings. However, in …
components and functionalities required for analyzing and operating buildings. However, in …
Wisefuse: Workload characterization and dag transformation for serverless workflows
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 …
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
Digital twins have emerged as a key technology for optimizing the performance of
engineering products and systems. High-fidelity numerical simulations constitute the …
engineering products and systems. High-fidelity numerical simulations constitute the …
Collaborative filtering integrated fine-grained sentiment for hybrid recommender system
Develo** online educational platforms necessitates the incorporation of new intelligent
procedures in order to improve long-term student experience. Presently, e-learning …
procedures in order to improve long-term student experience. Presently, e-learning …
Single-pass top-N subgraph centrality of graphs via subspace projections
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 …
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 …
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 …
(HOSVD), is a popular method for approximating a tensor of order≥ 3 via a smaller core …
Counting Triangles of Graphs via Matrix Partitioning
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 …
related metrics such as transitivity ratio, link recommendation, near-clique subgraph …
Fast Updating Truncated SVD for Representation Learning with Sparse Matrices
Updating a truncated Singular Value Decomposition (SVD) is crucial in representation
learning, especially when dealing with large-scale data matrices that continuously evolve in …
learning, especially when dealing with large-scale data matrices that continuously evolve in …
Dynamic Collaborative Filtering for Matrix-and Tensor-based Recommender Systems
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 …
update models in real-time. Many recommender models often require complete retraining to …