We introduce a class of robust non-parametric estimation methods which are ideally suited for the reconstruction of signals and images from noise-corrupted or sparsely collected s...
Performing random walks in networks is a fundamental primitive that has found applications in many areas of computer science, including distributed computing. In this paper, we fo...
Atish Das Sarma, Danupon Nanongkai, Gopal Panduran...
Monte Carlo analysis has so far been the corner stone for analog statistical simulations. Fast and accurate simulations are necessary for stringent time-to-market, design for manu...
The likelihood models used in probabilistic visual tracking applications are often complex non-linear and/or nonGaussian functions, leading to analytically intractable inference. ...
This paper proposes a new method of designing finitesupport wavelet filters, based on minimization of energy in key parts of the frequency domain. In particular this technique is ...