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» On Approximating Real-World Halting Problems
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SDM
2010
SIAM
200views Data Mining» more  SDM 2010»
13 years 9 months ago
Residual Bayesian Co-clustering for Matrix Approximation
In recent years, matrix approximation for missing value prediction has emerged as an important problem in a variety of domains such as recommendation systems, e-commerce and onlin...
Hanhuai Shan, Arindam Banerjee
ICML
2008
IEEE
14 years 8 months ago
Learning to classify with missing and corrupted features
After a classifier is trained using a machine learning algorithm and put to use in a real world system, it often faces noise which did not appear in the training data. Particularl...
Ofer Dekel, Ohad Shamir
TNN
2010
173views Management» more  TNN 2010»
13 years 2 months ago
Multiclass relevance vector machines: sparsity and accuracy
Abstract--In this paper we investigate the sparsity and recognition capabilities of two approximate Bayesian classification algorithms, the multi-class multi-kernel Relevance Vecto...
Ioannis Psorakis, Theodoros Damoulas, Mark A. Giro...
EDBT
2008
ACM
125views Database» more  EDBT 2008»
14 years 7 months ago
On the brink: searching for drops in sensor data
Sensor networks have been widely used to collect data about the environment. When analyzing data from these systems, people tend to ask exploratory questions--they want to find su...
Gong Chen, Junghoo Cho, Mark H. Hansen
ESANN
2004
13 years 9 months ago
Neural dynamics for task-oriented grouping of communicating agents
Abstract. Many real world problems are given in the form of multiple measurements comprising local descriptions or tasks. We propose that a dynamical organization of a population o...
Jochen J. Steil