Abstract—We propose a robust fitting framework, called Adaptive Kernel-Scale Weighted Hypotheses (AKSWH), to segment multiplestructure data even in the presence of a large number...
For many types of machine learning algorithms, one can compute the statistically optimal" way to select training data. In this paper, we review how optimal data selection tec...
David A. Cohn, Zoubin Ghahramani, Michael I. Jorda...
We present a probabilistic model-based framework for distributed learning that takes into account privacy restrictions and is applicable to scenarios where the different sites ha...
We propose a novel Partition Path-Based (PPB) grouping strategy to store compressed XML data in a stream of blocks. In addition, we employ a minimal indexing scheme called Block S...
Utility provisioning, Grid resource management, instant copy kiosks, and network transfers provide an exciting new paradigm for data warehouse functions. Grid technologies are fas...