—This paper compares parallel and distributed implementations of an iterative, Gibbs sampling, machine learning algorithm. Distributed implementations run under Hadoop on facilit...
Sebastien Bratieres, Jurgen Van Gael, Andreas Vlac...
We investigate in this article the rigid registration of large sets of points, generally sampled from surfaces. We formulate this problem as a general Maximum-Likelihood (ML) estim...
Clouds are emerging as an important class of distributed computational resources and are quickly becoming an integral part of production computational infrastructures. An importan...
Hyunjoo Kim, Yaakoub El Khamra, Shantenu Jha, Mani...
Hadoop has become a critical component in today’s cloud environment. Ensuring good performance for Hadoop is paramount for the wide-range of applications built on top of it. In ...
Batched stream processing is a new distributed data processing paradigm that models recurring batch computations on incrementally bulk-appended data streams. The model is inspired...
Bingsheng He, Mao Yang, Zhenyu Guo, Rishan Chen, B...