Spectral unmixing is an important task for remotely sensed hyperspectral data exploitation. Linear spectral unmixing relies on two main steps: 1) identification of pure spectral c...
Abstract. In this paper, we incorporated the global convex segmentation method and the split Bregman technique into the region-scalable fitting energy model. The new proposed metho...
Yunyun Yang, Chunming Li, Chiu-Yen Kao, Stanley Os...
The usage of optimistic version control systems comes along with cumbersome and time-consuming conflict resolution in the case that the modifications of two developers are contrad...
We consider the problem of numerical stability and model density growth when training a sparse linear model from massive data. We focus on scalable algorithms that optimize certain...
Abstract. We present an implementation of model-based online reinforcement learning (RL) for continuous domains with deterministic transitions that is specifically designed to achi...