A method is presented for e cient and reliable object recognition within noisy, cluttered, and occluded range images. The method is based on a strategy which hypothesizes the inte...
Large amount of uncertain data is inherent in many novel and important applications such as sensor data analysis and mobile data management. A probabilistic threshold range aggrega...
We present an adaptive distributed query-sampling framework that is quality-conscious for extracting high-quality text database samples. The framework divides the query-based samp...
Abstract. Feature selection in reinforcement learning (RL), i.e. choosing basis functions such that useful approximations of the unkown value function can be obtained, is one of th...
The volume of stream data delivered from different information sources is increasing. There are a variety of demands to utilize such stream data for applications. Stream processin...