For half a century since computers came into existence, the goal of finding elegant and efficient algorithms to solve "simple" (welldefined and well-structured) problems ...
—The pairwise constraints specifying whether a pair of samples should be grouped together or not have been successfully incorporated into the conventional clustering methods such...
We present a novel semi-supervised training algorithm for learning dependency parsers. By combining a supervised large margin loss with an unsupervised least squares loss, a discr...
Compressive sampling offers a new paradigm for acquiring signals that are compressible with respect to an orthonormal basis. The major algorithmic challenge in compressive sampling...
In this paper, we propose an energy-based technique to track the power of multiple simultaneous speakers using an ad hoc microphone array with unknown microphone positions. By con...