We introduce a variational inference framework for training the Gaussian process latent variable model and thus performing Bayesian nonlinear dimensionality reduction. This method...
This paper highlights the growing importance of storage energy consumption in a typical data center, and asserts that storage energy research should drive towards a vision of ener...
Jorge Guerra, Wendy Belluomini, Joseph S. Glider, ...
Abstract--In this paper we investigate the sparsity and recognition capabilities of two approximate Bayesian classification algorithms, the multi-class multi-kernel Relevance Vecto...
Ioannis Psorakis, Theodoros Damoulas, Mark A. Giro...
Mobile phone data provides rich dynamic information on human activities in social network analysis. In this paper, we represent data from two different modalities as a graph and f...
Xiaowen Dong, Pascal Frossard, Pierre Vandergheyns...
In this paper, we propose a new methodology for detecting lane markers that exploits the parallel nature of lane boundaries on the road. First, the input image is pre-processed an...