Principal component analysis (PCA) is a classical data analysis technique that finds linear transformations of data that retain the maximal amount of variance. We study a case whe...
In Proc. of IEEE Conf. on CVPR'2000, Vol.I, pp.222-227, Hilton Head Island, SC, 2000 In many vision applications, the practice of supervised learning faces several difficulti...
We present an improvement to Harvey and Ginsberg's limited discrepancy search algorithm, which eliminates much of the redundancy in the original, by generating each path from...
Abstract. Zigzag pocket machining (or 2D-milling) plays an important role in the manufacturing industry. The objective is to minimize the number of tool retractions in the zigzag m...
Danny Z. Chen, Rudolf Fleischer, Jian Li, Haitao W...
Abstract--In experimental and observational sciences, detecting atypical, peculiar data from large sets of measurements has the potential of highlighting candidates of interesting ...