The big challenge related to the contemporary research on ubiquitous and pervasive computing is that of seamless integration. For the next generation of ubiquitous and distributed...
We propose a new robust estimator for parameter estimation in highly noisy data with multiple structures and without prior information on the noise scale of inliers. This is a diag...
Trung Ngo Thanh, Hajime Nagahara, Ryusuke Sagawa, ...
Advances in wireless vehicular networks present us with opportunities for developing new distributed traffic control algorithms that avoid phenomena such as abrupt phase-transition...
We consider the problem of boosting the accuracy of weak learning algorithms in the agnostic learning framework of Haussler (1992) and Kearns et al. (1992). Known algorithms for t...
We introduce methods for optimizing physics-based walking controllers for robustness to uncertainty. Many unknown factors, such as external forces, control torques, and user contr...