Abstract-- Local convergence is a limitation of many optimization approaches for multimodal functions. For hybrid model learning, this can mean a compromise in accuracy. We develop...
The problem of maximizing system utility by allocating a single finite resource to satisfy discrete Quality of Service (QoS) requirements of multiple applications along multiple Q...
Chen Lee, John P. Lehoczky, Daniel P. Siewiorek, R...
Existing autocalibration techniques use numerical optimization algorithms that are prone to the problem of local minima. To address this problem, we have developed a method where ...
Abstract— In this paper we show how to optimize the computational cost and maximize consistency in EKF-based SLAM for large environments. We combine Local Mapping with Map Joinin...
: Nowadays, solving nonsmooth (not necessarily differentiable) optimization problems plays a very important role in many areas of industrial applications. Most of the algorithms d...