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» Set cover algorithms for very large datasets
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CVPR
2010
IEEE
16 years 12 days 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 2 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 5 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 8 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 8 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