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» A New Approximate Maximal Margin Classification Algorithm
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VMV
2008
120views Visualization» more  VMV 2008»
13 years 9 months ago
Thinning Mesh Animations
Three-dimensional animation sequences are often represented by a discrete set of compatible triangle meshes. In order to create the illusion of a smooth motion, a sequence usually...
Tim Winkler, Jens Drieseberg, Kai Hormann, Alexand...
KDD
2004
ACM
166views Data Mining» more  KDD 2004»
14 years 8 months ago
Predicting prostate cancer recurrence via maximizing the concordance index
In order to effectively use machine learning algorithms, e.g., neural networks, for the analysis of survival data, the correct treatment of censored data is crucial. The concordan...
Lian Yan, David Verbel, Olivier Saidi
SDM
2008
SIAM
150views Data Mining» more  SDM 2008»
13 years 9 months ago
A Stagewise Least Square Loss Function for Classification
This paper presents a stagewise least square (SLS) loss function for classification. It uses a least square form within each stage to approximate a bounded monotonic nonconvex los...
Shuang-Hong Yang, Bao-Gang Hu
SODA
2010
ACM
208views Algorithms» more  SODA 2010»
14 years 5 months ago
Correlation Robust Stochastic Optimization
We consider a robust model proposed by Scarf, 1958, for stochastic optimization when only the marginal probabilities of (binary) random variables are given, and the correlation be...
Shipra Agrawal, Yichuan Ding, Amin Saberi, Yinyu Y...
NN
2000
Springer
192views Neural Networks» more  NN 2000»
13 years 7 months ago
A new algorithm for learning in piecewise-linear neural networks
Piecewise-linear (PWL) neural networks are widely known for their amenability to digital implementation. This paper presents a new algorithm for learning in PWL networks consistin...
Emad Gad, Amir F. Atiya, Samir I. Shaheen, Ayman E...