High-dimensional statistical inference deals with models in which the the number of parameters p is comparable to or larger than the sample size n. Since it is usually impossible ...
Sahand Negahban, Pradeep Ravikumar, Martin J. Wain...
With the development of World Wide Web (WWW), storage and utilization of web data has become a big challenge for data management research community. Web data are essentially hetero...
In this paper, we investigate the survivability of mobile wireless communication networks in the event of base station (BS) failure. A survivable network is modeled as a mathemati...
We study human decision making in a simple forced-choice task that manipulates the frequency and accuracy of available information. Empirically, we find that people make decisions...
We propose a highly efficient framework for penalized likelihood kernel methods applied to multiclass models with a large, structured set of classes. As opposed to many previous a...