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NIPS
2003
13 years 9 months ago
Learning the k in k-means
When clustering a dataset, the right number k of clusters to use is often not obvious, and choosing k automatically is a hard algorithmic problem. In this paper we present an impr...
Greg Hamerly, Charles Elkan
AAAI
1998
13 years 9 months ago
Learning to Classify Text from Labeled and Unlabeled Documents
In many important text classification problems, acquiring class labels for training documents is costly, while gathering large quantities of unlabeled data is cheap. This paper sh...
Kamal Nigam, Andrew McCallum, Sebastian Thrun, Tom...
JMLR
2002
106views more  JMLR 2002»
13 years 7 months ago
Some Greedy Learning Algorithms for Sparse Regression and Classification with Mercer Kernels
We present some greedy learning algorithms for building sparse nonlinear regression and classification models from observational data using Mercer kernels. Our objective is to dev...
Prasanth B. Nair, Arindam Choudhury 0002, Andy J. ...
CVPR
2009
IEEE
1081views Computer Vision» more  CVPR 2009»
15 years 2 months ago
Learning Real-Time MRF Inference for Image Denoising
Many computer vision problems can be formulated in a Bayesian framework with Markov Random Field (MRF) or Conditional Random Field (CRF) priors. Usually, the model assumes that ...
Adrian Barbu (Florida State University)
CHI
2005
ACM
14 years 8 months ago
Learning user interest for image browsing on small-form-factor devices
Mobile devices which can capture and view pictures are becoming increasingly common in our life. The limitation of these small-form-factor devices makes the user experience of ima...
Xing Xie, Hao Liu, Simon Goumaz, Wei-Ying Ma