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UAI
2003
13 years 10 months ago
On Information Regularization
We formulate a principle for classification with the knowledge of the marginal distribution over the data points (unlabeled data). The principle is cast in terms of Tikhonov styl...
Adrian Corduneanu, Tommi Jaakkola
BMCBI
2010
119views more  BMCBI 2010»
13 years 9 months ago
Multi-task learning for cross-platform siRNA efficacy prediction: an in-silico study
Background: Gene silencing using exogenous small interfering RNAs (siRNAs) is now a widespread molecular tool for gene functional study and new-drug target identification. The key...
Qi Liu, Qian Xu, Vincent Wenchen Zheng, Hong Xue, ...
IPMI
2007
Springer
14 years 9 months ago
Shape Regression Machine
Abstract. We present a machine learning approach called shape regression machine (SRM) to segmenting in real time an anatomic structure that manifests a deformable shape in a medic...
Shaohua Kevin Zhou, Dorin Comaniciu
ML
2002
ACM
178views Machine Learning» more  ML 2002»
13 years 8 months ago
Metric-Based Methods for Adaptive Model Selection and Regularization
We present a general approach to model selection and regularization that exploits unlabeled data to adaptively control hypothesis complexity in supervised learning tasks. The idea ...
Dale Schuurmans, Finnegan Southey
ALT
2009
Springer
14 years 5 months ago
Approximation Algorithms for Tensor Clustering
Abstract. We present the first (to our knowledge) approximation algorithm for tensor clustering—a powerful generalization to basic 1D clustering. Tensors are increasingly common...
Stefanie Jegelka, Suvrit Sra, Arindam Banerjee