This paper addresses the supervised learning in which the class membership of training data are subject to uncertainty. This problem is tackled in the framework of the Dempster-Sha...
The goal of frequent subgraph mining is to detect subgraphs that frequently occur in a dataset of graphs. In classification settings, one is often interested in discovering discr...
Marisa Thoma, Hong Cheng, Arthur Gretton, Jiawei H...
As it becomes increasingly viable to capture, store, and share large amounts of image and video data, automatic image analysis is crucial to managing visual information. Many prob...
This paper proposes a convolution forest kernel to effectively explore rich structured features embedded in a packed parse forest. As opposed to the convolution tree kernel, the p...
Abstract--Phase-Change Random Access Memory (PRAM) has become one of the most promising emerging memory technologies, due to its attractive features such as high density, fast acce...