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NIPS
2008
14 years 18 days ago
Clustered Multi-Task Learning: A Convex Formulation
In multi-task learning several related tasks are considered simultaneously, with the hope that by an appropriate sharing of information across tasks, each task may benefit from th...
Laurent Jacob, Francis Bach, Jean-Philippe Vert
ICCV
2009
IEEE
15 years 4 months ago
TagProp: Discriminative Metric Learning in Nearest Neighbor Models for Image Auto-Annotation
Image auto-annotation is an important open problem in computer vision. For this task we propose TagProp, a discriminatively trained nearest neighbor model. Tags of test images a...
Matthieu Guillaumin, Thomas Mensink, Jakob Verbeek...
ESAS
2006
Springer
14 years 2 months ago
Dynamics of Learning Algorithms for the On-Demand Secure Byzantine Routing Protocol
We investigate the performance of of several protocol enhancements to the On-Demand Secure Byzantine Routing (ODSBR) [3] protocol in the presence of various Byzantine Attack models...
Baruch Awerbuch, Robert G. Cole, Reza Curtmola, Da...
SODA
2001
ACM
79views Algorithms» more  SODA 2001»
14 years 16 days ago
Learning Markov networks: maximum bounded tree-width graphs
Markov networks are a common class of graphical models used in machine learning. Such models use an undirected graph to capture dependency information among random variables in a ...
David R. Karger, Nathan Srebro
ICASSP
2008
IEEE
14 years 5 months ago
Multiple kernel learning for speaker verification
Many speaker verification (SV) systems combine multiple classifiers using score-fusion to improve system performance. For SVM classifiers, an alternative strategy is to combine...
Chris Longworth, Mark J. F. Gales