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NIPS
2004
15 years 6 months ago
Support Vector Classification with Input Data Uncertainty
This paper investigates a new learning model in which the input data is corrupted with noise. We present a general statistical framework to tackle this problem. Based on the stati...
Jinbo Bi, Tong Zhang
NIPS
2003
15 years 6 months ago
Prediction on Spike Data Using Kernel Algorithms
We report and compare the performance of different learning algorithms based on data from cortical recordings. The task is to predict the orientation of visual stimuli from the ac...
Jan Eichhorn, Andreas S. Tolias, Alexander Zien, M...
137
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ICML
2010
IEEE
15 years 6 months ago
Variable Selection in Model-Based Clustering: To Do or To Facilitate
Variable selection for cluster analysis is a difficult problem. The difficulty originates not only from the lack of class information but also the fact that high-dimensional data ...
Leonard K. M. Poon, Nevin Lianwen Zhang, Tao Chen,...
ISBI
2008
IEEE
16 years 6 months ago
Sparse representations for limited data tomography
In limited data tomography, with applications such as electron microscopy and medical imaging, the scanning views are within an angular range that is often both limited and sparse...
Hstau Y. Liao, Guillermo Sapiro
KDD
2010
ACM
282views Data Mining» more  KDD 2010»
15 years 9 months ago
Optimizing debt collections using constrained reinforcement learning
In this paper, we propose and develop a novel approach to the problem of optimally managing the tax, and more generally debt, collections processes at financial institutions. Our...
Naoki Abe, Prem Melville, Cezar Pendus, Chandan K....