As semiconductor processing technology continues to scale down, managing reliability becomes an increasingly difficult challenge in high-performance microprocessor design. Transie...
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, ...
An autonomous variational inference algorithm for arbitrary graphical models requires the ability to optimize variational approximations over the space of model parameters as well...
—While computing speed continues increasing rapidly, data-access technology is lagging behind. Data-access delay, not the processor speed, becomes the leading performance bottlen...
We consider a framework for semi-supervised learning using spectral decomposition-based unsupervised kernel design. We relate this approach to previously proposed semi-supervised l...