A self-adaptive regularized alternating least squares method for tensor decomposition problems
Sign Up to like & getrecommendations! Published in 2019 at "Analysis and Applications"
DOI: 10.1142/s0219530519410057
Abstract: Though the alternating least squares algorithm (ALS), as a classic and easily implemented algorithm, has been widely applied to tensor decomposition and approximation problems, it has some drawback... read more here.
Keywords: tensor decomposition; least squares; self adaptive; alternating least ... See more keywords
Smart and Rapid Design of Nanophotonic Structures by an Adaptive and Regularized Deep Neural Network
Sign Up to like & getrecommendations! Published in 2022 at "Nanomaterials"
DOI: 10.3390/nano12081372
Abstract: The design of nanophotonic structures based on deep learning is emerging rapidly in the research community. Design methods using Deep Neural Networks (DNN) are outperforming conventional physics-based simulations performed iteratively by human experts. Here, a… read more here.
Keywords: nanophotonic structures; lrs rcnn; deep neural; design nanophotonic ... See more keywords