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KDD
2009
ACM
180views Data Mining» more  KDD 2009»
16 years 12 days ago
Using graph-based metrics with empirical risk minimization to speed up active learning on networked data
Active and semi-supervised learning are important techniques when labeled data are scarce. Recently a method was suggested for combining active learning with a semi-supervised lea...
Sofus A. Macskassy
KDD
2009
ACM
198views Data Mining» more  KDD 2009»
16 years 12 days ago
Pervasive parallelism in data mining: dataflow solution to co-clustering large and sparse Netflix data
All Netflix Prize algorithms proposed so far are prohibitively costly for large-scale production systems. In this paper, we describe an efficient dataflow implementation of a coll...
Srivatsava Daruru, Nena M. Marin, Matt Walker, Joy...
MOBISYS
2009
ACM
16 years 12 days ago
SoundSense: scalable sound sensing for people-centric applications on mobile phones
Top end mobile phones include a number of specialized (e.g., accelerometer, compass, GPS) and general purpose sensors (e.g., microphone, camera) that enable new people-centric sen...
Hong Lu, Wei Pan, Nicholas D. Lane, Tanzeem Choudh...
MOBISYS
2009
ACM
16 years 12 days ago
R2D2: regulating beam shape and rate as directionality meets diversity
We design, implement, and evaluate a vehicular communication system that improves uplink connectivity through multi-lobe beam pattern switching on a smart antenna. Directionality ...
Kishore Ramachandran, Ravi Kokku, Karthikeyan Sund...
KDD
2008
ACM
181views Data Mining» more  KDD 2008»
16 years 8 days ago
Learning subspace kernels for classification
Kernel methods have been applied successfully in many data mining tasks. Subspace kernel learning was recently proposed to discover an effective low-dimensional subspace of a kern...
Jianhui Chen, Shuiwang Ji, Betul Ceran, Qi Li, Min...