Zobrazeno 1 - 3
of 3
pro vyhledávání: '"Soh, Yongseok"'
Autor:
Laukemann, Jan, Helal, Ahmed E., Anderson, S. Isaac Geronimo, Checconi, Fabio, Soh, Yongseok, Tithi, Jesmin Jahan, Ranadive, Teresa, Gravelle, Brian J, Petrini, Fabrizio, Choi, Jee
High-dimensional sparse data emerge in many critical application domains such as cybersecurity, healthcare, anomaly detection, and trend analysis. To quickly extract meaningful insights from massive volumes of these multi-dimensional data, scientists
Externí odkaz:
http://arxiv.org/abs/2403.06348
Autor:
Nguyen, Andy, Helal, Ahmed E., Checconi, Fabio, Laukemann, Jan, Tithi, Jesmin Jahan, Soh, Yongseok, Ranadive, Teresa, Petrini, Fabrizio, Choi, Jee W.
Tensor decomposition (TD) is an important method for extracting latent information from high-dimensional (multi-modal) sparse data. This study presents a novel framework for accelerating fundamental TD operations on massively parallel GPU architectur
Externí odkaz:
http://arxiv.org/abs/2201.12523
Publikováno v:
Proceedings of SPIE; February 2012, Vol. 8290 Issue: 1 p82900D-82900D-10, 8207111p
