Loopy and generalized belief propagation are popular algorithms for approximate inference in Markov random fields and Bayesian networks. Fixed points of these algorithms have been...
We study randomized variants of two classical algorithms: coordinate descent for systems of linear equations and iterated projections for systems of linear inequalities. Expanding...
In this paper, we study the theoretical problem of the end-to-end rate assignment for multi-hop wireless networks. Specifically, we consider the problem of joint congestion control...
Chengnian Long, Bo Li, Qian Zhang, Bin Zhao, Bo Ya...
— In this paper, we show that one-class SVMs can also utilize data covariance in a robust manner to improve performance. Furthermore, by constraining the desired kernel function ...
We introduce two new methods for the demodulation of acoustic signals by posing the problem in a convex optimization framework. This allows the parameters of the modulator and carr...