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NIPS
2007
15 years 8 months ago
Multi-Task Learning via Conic Programming
When we have several related tasks, solving them simultaneously is shown to be more effective than solving them individually. This approach is called multi-task learning (MTL) and...
Tsuyoshi Kato, Hisashi Kashima, Masashi Sugiyama, ...
IJCAI
2003
15 years 8 months ago
When Discriminative Learning of Bayesian Network Parameters Is Easy
Bayesian network models are widely used for discriminative prediction tasks such as classification. Usually their parameters are determined using 'unsupervised' methods ...
Hannes Wettig, Peter Grünwald, Teemu Roos, Pe...
189
Voted
ML
2002
ACM
127views Machine Learning» more  ML 2002»
15 years 6 months ago
Sparse Regression Ensembles in Infinite and Finite Hypothesis Spaces
We examine methods for constructing regression ensembles based on a linear program (LP). The ensemble regression function consists of linear combinations of base hypotheses generat...
Gunnar Rätsch, Ayhan Demiriz, Kristin P. Benn...
224
Voted
IJCV
2010
158views more  IJCV 2010»
15 years 5 months ago
Metric Learning for Image Alignment
Abstract Image alignment has been a long standing problem in computer vision. Parameterized Appearance Models (PAMs) such as the Lucas-Kanade method, Eigentracking, and Active Appe...
Minh Hoai Nguyen, Fernando De la Torre
IEAAIE
2010
Springer
15 years 4 months ago
Constructive Neural Networks to Predict Breast Cancer Outcome by Using Gene Expression Profiles
Abstract. Gene expression profiling strategies have attracted considerable interest from biologist due to the potential for high throughput analysis of hundreds of thousands of gen...
Daniel Urda, José Luis Subirats, Leonardo F...