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» Classification on Data with Biased Class Distribution
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ICML
2010
IEEE
13 years 8 months ago
Deep Supervised t-Distributed Embedding
Deep learning has been successfully applied to perform non-linear embedding. In this paper, we present supervised embedding techniques that use a deep network to collapse classes....
Martin Renqiang Min, Laurens van der Maaten, Zinen...
PAKDD
2004
ACM
97views Data Mining» more  PAKDD 2004»
14 years 1 months ago
Further Applications of a Particle Visualization Framework
Our previous work introduced a 3D particle visualization framework that viewed each data point as being a particle affected by gravitational forces. We showed the use of this tool ...
Ke Yin, Ian Davidson
NIPS
2004
13 years 9 months ago
Neighbourhood Components Analysis
In this paper we propose a novel method for learning a Mahalanobis distance measure to be used in the KNN classification algorithm. The algorithm directly maximizes a stochastic v...
Jacob Goldberger, Sam T. Roweis, Geoffrey E. Hinto...
ICML
2007
IEEE
14 years 8 months ago
Self-taught learning: transfer learning from unlabeled data
We present a new machine learning framework called "self-taught learning" for using unlabeled data in supervised classification tasks. We do not assume that the unlabele...
Rajat Raina, Alexis Battle, Honglak Lee, Benjamin ...
SDM
2008
SIAM
177views Data Mining» more  SDM 2008»
13 years 9 months ago
Roughly Balanced Bagging for Imbalanced Data
Imbalanced class problems appear in many real applications of classification learning. We propose a novel sampling method to improve bagging for data sets with skewed class distri...
Shohei Hido, Hisashi Kashima