Learning to cope with domain change has been known
as a challenging problem in many real-world applications.
This paper proposes a novel and efficient approach, named
domain ada...
Yu-Gang Jiang, Jun Wang, Shih-Fu Chang, Chong-Wah ...
Abstract. This paper proposes a new approach to learning a discriminative model of object classes, incorporating appearance, shape and context information efficiently. The learned ...
Jamie Shotton, John M. Winn, Carsten Rother, Anton...
With more and more commercial activities moving onto the Internet, people tend to purchase what they need through Internet or conduct some online research before the actual transac...
In USA, 2002, approximately 3.2 million intersection-related crashes occurred, corresponding to 50 percent of all reported crashes. In Japan, more than 58 percent of all traffic cr...
Flora Dilys Salim, Shonali Krishnaswamy, Seng Wai ...
This paper investigates the problem of automatically learning how to restructure the reward function of a Markov decision process so as to speed up reinforcement learning. We begi...