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NIPS
2007
15 years 6 months ago
Random Features for Large-Scale Kernel Machines
To accelerate the training of kernel machines, we propose to map the input data to a randomized low-dimensional feature space and then apply existing fast linear methods. The feat...
Ali Rahimi, Benjamin Recht
TSD
2007
Springer
15 years 10 months ago
On the Relative Hardness of Clustering Corpora
Abstract. Clustering is often considered the most important unsupervised learning problem and several clustering algorithms have been proposed over the years. Many of these algorit...
David Pinto, Paolo Rosso
INFORMATICALT
2008
124views more  INFORMATICALT 2008»
15 years 4 months ago
Hierarchical Adaptive Clustering
This paper studies an adaptive clustering problem. We focus on re-clustering an object set, previously clustered, when the feature set characterizing the objects increases. We prop...
Gabriela Serban, Alina Campan
CLUSTER
2007
IEEE
15 years 11 months ago
Non-collective parallel I/O for global address space programming models
— Achieving high performance for out-of-core applications typically involves explicit management of the movement of data between the disk and the physical memory. We are developi...
Sriram Krishnamoorthy, Juan Piernas, Vinod Tippara...
ACL
2008
15 years 6 months ago
Which Are the Best Features for Automatic Verb Classification
In this work, we develop and evaluate a wide range of feature spaces for deriving Levinstyle verb classifications (Levin, 1993). We perform the classification experiments using Ba...
Jianguo Li, Chris Brew