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» On Approximating Real-World Halting Problems
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SDM
2010
SIAM
200views Data Mining» more  SDM 2010»
15 years 4 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
16 years 4 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»
14 years 10 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»
16 years 3 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
15 years 4 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