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ICDCS
2002
IEEE
14 years 10 days ago
A Fully Distributed Framework for Cost-Sensitive Data Mining
Data mining systems aim to discover patterns and extract useful information from facts recorded in databases. A widely adopted approach is to apply machine learning algorithms to ...
Wei Fan, Haixun Wang, Philip S. Yu, Salvatore J. S...
ICSE
2004
IEEE-ACM
14 years 7 months ago
Managing Commitments and Risks: Challenges in Distributed Agile Development
Software development is always a challenging undertaking and it requires high commitments from individuals who participate in it. Software development often involves new technolog...
Jan Rydén, Jyrki Kontio, Magnus Höglun...
ICRA
2008
IEEE
134views Robotics» more  ICRA 2008»
14 years 1 months ago
Real-time learning of resolved velocity control on a Mitsubishi PA-10
Abstract— Learning inverse kinematics has long been fascinating the robot learning community. While humans acquire this transformation to complicated tool spaces with ease, it is...
Jan Peters, Duy Nguyen-Tuong
NIPS
2007
13 years 8 months ago
Distributed Inference for Latent Dirichlet Allocation
We investigate the problem of learning a widely-used latent-variable model – the Latent Dirichlet Allocation (LDA) or “topic” model – using distributed computation, where ...
David Newman, Arthur Asuncion, Padhraic Smyth, Max...
CAISE
2003
Springer
14 years 19 days ago
Distributed Data Clustering
Abstract. To make effective use of distributed information, it is desirable to allow coordination and collaboration among various information sources. This paper deals with cluster...
Abdelhamid Bouchachia