Dynamic Network Representation Based on Latent Factorization of Tensors

Explore the cutting-edge insights in "Dynamic Network Representation Based on Latent Factorization of Tensors" by Hao Wu, published by Springer Verlag in 2023. This first edition, comprising 80 pages, delves into advanced methodologies for modeling dynamic networks with unparalleled precision and efficiency. Utilizing an innovative alternating direction method of multipliers framework, this book presents a robust learning model that significantly enhances network representation. Ideal for researchers and professionals in the field, Wu’s work is a vital resource for anyone looking to deepen their understanding of dynamic network analysis. Discover how latent factorization of tensors can transform your approach to complex network structures. Elevate your knowledge and stay ahead in the rapidly evolving landscape of network representation with this essential guide.