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cs.LG2019
SENSE: Semantically Enhanced Node Sequence Embedding
Swati Rallapalli, Liang Ma, Mudhakar Srivatsa +4
Effectively capturing graph node sequences in the form of vector embeddings is critical to many applications. We achieve this by (i) first learning vector embeddings of single grap…
cs.LG2015
Optimal Sparse Kernel Learning for Hyperspectral Anomaly Detection
Zhimin Peng, Prudhvi Gurram, Heesung Kwon +1
In this paper, a novel framework of sparse kernel learning for Support Vector Data Description (SVDD) based anomaly detection is presented. In this work, optimal sparse feature sel…