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» Evaluating algorithms that learn from data streams
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KDD
2006
ACM
156views Data Mining» more  KDD 2006»
16 years 7 months ago
Unsupervised learning on k-partite graphs
Various data mining applications involve data objects of multiple types that are related to each other, which can be naturally formulated as a k-partite graph. However, the resear...
Bo Long, Xiaoyun Wu, Zhongfei (Mark) Zhang, Philip...
IJON
2008
186views more  IJON 2008»
15 years 6 months ago
Computational analysis and learning for a biologically motivated model of boundary detection
In this work we address the problem of boundary detection by combining ideas and approaches from biological and computational vision. Initially, we propose a simple and efficient ...
Iasonas Kokkinos, Rachid Deriche, Olivier D. Fauge...
IJAR
2006
118views more  IJAR 2006»
15 years 6 months ago
Learning Bayesian network parameters under order constraints
We consider the problem of learning the parameters of a Bayesian network from data, while taking into account prior knowledge about the signs of influences between variables. Such...
A. J. Feelders, Linda C. van der Gaag
ICML
2001
IEEE
16 years 7 months ago
Off-Policy Temporal Difference Learning with Function Approximation
We introduce the first algorithm for off-policy temporal-difference learning that is stable with linear function approximation. Off-policy learning is of interest because it forms...
Doina Precup, Richard S. Sutton, Sanjoy Dasgupta
IDA
2011
Springer
15 years 1 months ago
Ubiquitous Knowledge Discovery
Ubiquitous Knowledge Discovery is a new research area at the intersection of machine learning and data mining with mobile and distributed systems. In this paper the main character...
João Gama, Michael May