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AAAI
2000
13 years 6 months ago
Selective Sampling with Redundant Views
Selective sampling, a form of active learning, reduces the cost of labeling training data by asking only for the labels of the most informative unlabeled examples. We introduce a ...
Ion Muslea, Steven Minton, Craig A. Knoblock
ICDM
2002
IEEE
448views Data Mining» more  ICDM 2002»
13 years 9 months ago
Feature Selection Algorithms: A Survey and Experimental Evaluation
In view of the substantial number of existing feature selection algorithms, the need arises to count on criteria that enables to adequately decide which algorithm to use in certai...
Luis Carlos Molina, Lluís Belanche, À...
ER
1999
Springer
155views Database» more  ER 1999»
13 years 9 months ago
Detecting Redundancy in Data Warehouse Evolution
A Data Warehouse DW can be abstractly seen as a set of materialized views de ned over a set of remote data sources. A DW is intended to satisfy a set of queries. The views materi...
Dimitri Theodoratos
NAACL
2003
13 years 6 months ago
Weakly Supervised Natural Language Learning Without Redundant Views
We investigate single-view algorithms as an alternative to multi-view algorithms for weakly supervised learning for natural language processing tasks without a natural feature spl...
Vincent Ng, Claire Cardie
WSCG
2004
143views more  WSCG 2004»
13 years 6 months ago
View Dependent Stochastic Sampling for Efficient Rendering of Point Sampled Surfaces
In this paper we present a new technique for rendering very large datasets representing point-sampled surfaces. Rendering efficiency is considerably improved by using stochastic s...
Sushil Bhakar, Liang Luo, Sudhir P. Mudur