… Transfer Learning (HHTL), which allows the corresponding instances across … a deep
learning approach to learn a feature mapping between crossdomain heterogeneous features as …

… In this paper, we propose a novel deep learning model to examine heterogeneous county-level
features and to predict growth of infected cases in the future. The proposed method can …

… To capture nonlinear relationships of heterogeneous features between domains, we also
construct neural networks with one hidden layer to approximate { G T , k } 's and { G S , k } 's, …

… (low-level and middle-level features). This study proposes a novel Lie Group deep learning
… and higher-level features from images based on Lie Group machine learning (LGML) and …

… Heterogeneous face matching is a challenge issue … deep learning (CDL) approach for the
heterogeneous face matching. CDL seeks a shared feature space in which the heterogeneous …

… a deep learning architecture can be designed for intelligent malware detection. We propose
a heterogeneous deep learning … The proposed deep learning model performs as a greedy …

… Motivated by the remarkable success of deep learning (DL) techniques in the fields of …
kernel learning (MKL) algorithm to process heterogeneous features in this paper. This deep …

… Our model for image feature extraction is pretrained with the … (2) Heterogeneous features
including deep features … first study to introduce into the deep learning CADx system the clinical …

… Although deep learning has yielded impressive … a deep heterogeneous feature fusion
network to exploit the complementary information present in features generated by different deep …

… learning model, called HGCN, to … heterogeneity of HINs, we design a novel heterogeneous
graph inception with the holistic HIN as the input, which not only balances relational features …