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» Efficient Discovery of Confounders in Large Data Sets
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AAAI
2008
15 years 8 months ago
Zero-data Learning of New Tasks
We introduce the problem of zero-data learning, where a model must generalize to classes or tasks for which no training data are available and only a description of the classes or...
Hugo Larochelle, Dumitru Erhan, Yoshua Bengio
ICC
2007
IEEE
186views Communications» more  ICC 2007»
16 years 21 days ago
An Efficient Cluster-Based Proactive Secret Share Update Scheme for Mobile Ad Hoc Networks
– When implementing public key security ser- easy for an adversary to collect data and attack. To solve this vices in mobile ad hoc networks (MANETs), multiple problem, the distr...
Ying Dong, Ai Fen Sui, Siu-Ming Yiu, Victor O. K. ...
BMCBI
2008
82views more  BMCBI 2008»
15 years 6 months ago
Standardized high-throughput evaluation of cell-based compound screens
Background: High-throughput screening of pharmaceutical compound activity in tissue culture experiments requires time-consuming repeated analysis of the large amounts of data gene...
Peter Frommolt, Roman K. Thomas
BMCBI
2010
182views more  BMCBI 2010»
15 years 6 months ago
L2-norm multiple kernel learning and its application to biomedical data fusion
Background: This paper introduces the notion of optimizing different norms in the dual problem of support vector machines with multiple kernels. The selection of norms yields diff...
Shi Yu, Tillmann Falck, Anneleen Daemen, Lé...
EDBT
2006
ACM
179views Database» more  EDBT 2006»
16 years 6 months ago
TrajPattern: Mining Sequential Patterns from Imprecise Trajectories of Mobile Objects
Abstract. Mobile objects have become ubiquitous in our everyday lives, ranging from cellular phones to sensors, therefore, analyzing and mining mobile data becomes an interesting p...
Jiong Yang, Meng Hu