Transfer learning proves to be effective for leveraging labeled data in the source domain to build an accurate classifier in the target domain. The basic assumption behind transf...
Mingsheng Long, Jianmin Wang 0001, Guiguang Ding, ...
Spectral feature selection identifies relevant features by measuring their capability of preserving sample similarity. It provides a powerful framework for both supervised and uns...
In this paper, a simple and effective tool for the design of low-density parity-check (LDPC) codes for iterative correction of bursts of erasures is presented. The design method co...
We introduce a computational framework for discovering regular or repeated geometric structures in 3D shapes. We describe and classify possible regular structures and present an e...
Mark Pauly, Niloy J. Mitra, Johannes Wallner, Helm...
The merit of automatic graph layout algorithms is typically judged by their computational efficiency and the extent to which they conform to aesthetic criteria (for example, minim...
Helen C. Purchase, Jo-Anne Allder, David A. Carrin...