8,010 research outputs found
GraphLab: A New Framework for Parallel Machine Learning
Designing and implementing efficient, provably correct parallel machine
learning (ML) algorithms is challenging. Existing high-level parallel
abstractions like MapReduce are insufficiently expressive while low-level tools
like MPI and Pthreads leave ML experts repeatedly solving the same design
challenges. By targeting common patterns in ML, we developed GraphLab, which
improves upon abstractions like MapReduce by compactly expressing asynchronous
iterative algorithms with sparse computational dependencies while ensuring data
consistency and achieving a high degree of parallel performance. We demonstrate
the expressiveness of the GraphLab framework by designing and implementing
parallel versions of belief propagation, Gibbs sampling, Co-EM, Lasso and
Compressed Sensing. We show that using GraphLab we can achieve excellent
parallel performance on large scale real-world problems
Priority-Based Conflict Resolution in Inconsistent Relational Databases
We study here the impact of priorities on conflict resolution in inconsistent
relational databases. We extend the framework of repairs and consistent query
answers. We propose a set of postulates that an extended framework should
satisfy and consider two instantiations of the framework: (locally preferred)
l-repairs and (globally preferred) g-repairs. We study the relationships
between them and the impact each notion of repair has on the computational
complexity of repair checking and consistent query answers
09351 Abstracts Collection -- Information processing, rational belief change and social interaction
From 23.08. to 27.08.2009, the Dagstuhl Seminar 09351 ``Information processing, rational belief change and social interaction \u27\u27 was held in Schloss Dagstuhl~--~Leibniz Center for Informatics.
During the seminar, several participants presented their current
research, and ongoing work and open problems were discussed. Abstracts of
the presentations given during the seminar as well as abstracts of
seminar results and ideas are put together in this paper. The first section
describes the seminar topics and goals in general.
Links to extended abstracts or full papers are provided, if available
Soldier system assessment under uncertainty with evidential reasoning
Along with the increasing of new equipment based capabilities, the physiological burden on the dismounted soldier keeps on growing, which leads to the limitation in the quantity and types of missions that can be carried out. In this research, a methodology is developed to solve the burden problem from
the system assessment point of view. Comparing with other relevant research, the new methodology not only provides quantitative performance estimate of the soldier with the capability of handling
fragmentary and incomplete data with hybrid format in nature (qualitative and quantitative), but also restrains the assessment complexity to an acceptable level
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