In this paper a concern about the accuracy (as a function of parallelism) of a certain class of distributed learning algorithms is raised, and one proposed improvement is illustrat...
Lawrence O. Hall, Nitesh V. Chawla, Kevin W. Bowye...
Abstract. There is an urgent need for sound approaches to integrative and collaborative analysis of large, autonomous (and hence, inevitably semantically heterogeneous) data source...
Doina Caragea, Jun Zhang 0002, Jyotishman Pathak, ...
Standard Reinforcement Learning (RL) aims to optimize decision-making rules in terms of the expected return. However, especially for risk-management purposes, other criteria such ...
With a few exceptions, discriminative training in statistical machine translation (SMT) has been content with tuning weights for large feature sets on small development data. Evid...
This paper presents a distributed Support Vector Machine (SVM) algorithm in order to detect malicious software (malware) on a network of mobile devices. The light-weight system mo...
Ashkan Sharifi Shamili, Christian Bauckhage, Tansu...