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KDD
2008
ACM
147views Data Mining» more  KDD 2008»
16 years 7 months ago
Structured learning for non-smooth ranking losses
Learning to rank from relevance judgment is an active research area. Itemwise score regression, pairwise preference satisfaction, and listwise structured learning are the major te...
Soumen Chakrabarti, Rajiv Khanna, Uma Sawant, Chir...
KDD
2010
ACM
245views Data Mining» more  KDD 2010»
15 years 8 months ago
Learning incoherent sparse and low-rank patterns from multiple tasks
We consider the problem of learning incoherent sparse and lowrank patterns from multiple tasks. Our approach is based on a linear multi-task learning formulation, in which the spa...
Jianhui Chen, Ji Liu, Jieping Ye
AICCSA
2006
IEEE
121views Hardware» more  AICCSA 2006»
15 years 8 months ago
Software Defect Prediction Using Regression via Classification
In this paper we apply a machine learning approach to the problem of estimating the number of defects called Regression via Classification (RvC). RvC initially automatically discr...
Stamatia Bibi, Grigorios Tsoumakas, Ioannis Stamel...
CVPR
2008
IEEE
16 years 8 months ago
Conditional density learning via regression with application to deformable shape segmentation
Many vision problems can be cast as optimizing the conditional probability density function p(C|I) where I is an image and C is a vector of model parameters describing the image. ...
Jingdan Zhang, Shaohua Kevin Zhou, Dorin Comaniciu...
205
Voted
LATA
2009
Springer
16 years 1 months ago
Hypothesis Spaces for Learning
In this paper we survey some results in inductive inference showing how learnability of a class of languages may depend on hypothesis space chosen. We also discuss results which co...
Sanjay Jain