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» Set cover algorithms for very large datasets
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CVPR
2010
IEEE
16 years 2 months ago
Detecting and Parsing Architecture at City Scale from Range Data
We present a method for detecting and parsing buildings from unorganized 3D point clouds into a compact, hierarchical representation that is useful for high-level tasks. The input...
Alexander Toshev, Philippos Mordohai, Ben Taskar

Book
778views
17 years 4 months ago
Gaussian Processes for Machine Learning
"Gaussian processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines. GPs have received increased attention in the machine-learning...
Carl Edward Rasmussen and Christopher K. I. Willia...
ACL
1998
15 years 7 months ago
Time Mapping with Hypergraphs
Word graphs are able to represent a large number of different utterance hypotheses in a very compact manner. However, usually they contain a huge amount of redundancy in terms of ...
Jan W. Amtrup, Volker Weber
BALT
2006
15 years 10 months ago
Introducing Softness into Inductive Queries on String Databases
In many application domains (e.g., WWW mining, molecular biology), large string datasets are available and yet under-exploited. The inductive database framework assumes that both s...
Ieva Mitasiunaite, Jean-François Boulicaut
AUSAI
2006
Springer
15 years 10 months ago
Voting Massive Collections of Bayesian Network Classifiers for Data Streams
Abstract. We present a new method for voting exponential (in the number of attributes) size sets of Bayesian classifiers in polynomial time with polynomial memory requirements. Tra...
Remco R. Bouckaert