We consider the general problem of learning from both labeled and unlabeled data. Given a set of data points, only a few of them are labeled, and the remaining points are unlabele...
Fei Wang, Changshui Zhang, Helen C. Shen, Jingdong...
— We consider a discrete-time dynamical system with Boolean and continuous states, with the continuous state propagating linearly in the continuous and Boolean state variables, a...
Argyris Zymnis, Stephen P. Boyd, Dimitry M. Gorine...
We present a novel family of data-driven linear transformations, aimed at visualizing multivariate data in a low-dimensional space in a way that optimally preserves the structure ...
Support vector (SV) machines are useful tools to classify populations characterized by abrupt decreases in density functions. At least for one class of Gaussian data model the SV ...
—In this paper, we propose a low complexity linear multiuser beamforming system for the multiple-input multipleoutput (MIMO) broadcast channel. We consider the specific case of ...
Chan-Byoung Chae, David Mazzarese, Nihar Jindal, R...