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» Modeling liaison in French by using decision trees
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ICML
2006
IEEE
14 years 9 months ago
Full Bayesian network classifiers
The structure of a Bayesian network (BN) encodes variable independence. Learning the structure of a BN, however, is typically of high computational complexity. In this paper, we e...
Jiang Su, Harry Zhang
SODA
2008
ACM
100views Algorithms» more  SODA 2008»
13 years 10 months ago
A tight lower bound for parity in noisy communication networks
We show a tight lower bound of (N log log N) on the number of transmission required to compute the parity of N bits (with constant error) in a network of N randomly placed sensors...
Chinmoy Dutta, Yashodhan Kanoria, D. Manjunath, Ja...
ICML
2006
IEEE
14 years 9 months ago
An empirical comparison of supervised learning algorithms
A number of supervised learning methods have been introduced in the last decade. Unfortunately, the last comprehensive empirical evaluation of supervised learning was the Statlog ...
Rich Caruana, Alexandru Niculescu-Mizil
VVS
1995
IEEE
132views Visualization» more  VVS 1995»
14 years 1 days ago
Multi-Dimensional Trees for Controlled Volume Rendering and Compression
This paper explores the use of multi-dimensional trees to provide spatial and temporal e ciencies in imaging large data sets. Each node of the tree contains a model of the data in...
Jane Wilhelms, Allen Van Gelder
MLMI
2004
Springer
14 years 1 months ago
Shallow Dialogue Processing Using Machine Learning Algorithms (or Not)
This paper presents a shallow dialogue analysis model, aimed at human-human dialogues in the context of staff or business meetings. Four components of the model are defined, and ...
Andrei Popescu-Belis, Alexander Clark, Maria Georg...