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ICPR
2004
IEEE
15 years 10 months ago
Selective Sampling Based on the Variation in Label Assignments
In this paper, a new selective sampling method for the active learning framework is presented. Initially, a small training set ? and a large unlabeled set ? are given. The goal is...
Piotr Juszczak, Robert P. W. Duin
CORR
2011
Springer
185views Education» more  CORR 2011»
14 years 4 months ago
Large-Scale Collective Entity Matching
There have been several recent advancements in Machine Learning community on the Entity Matching (EM) problem. However, their lack of scalability has prevented them from being app...
Vibhor Rastogi, Nilesh N. Dalvi, Minos N. Garofala...
NIPS
2004
14 years 11 months ago
Adaptive Manifold Learning
Recently, there have been several advances in the machine learning and pattern recognition communities for developing manifold learning algorithms to construct nonlinear low-dimen...
Jing Wang, Zhenyue Zhang, Hongyuan Zha
93
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COLT
2005
Springer
15 years 3 months ago
General Polynomial Time Decomposition Algorithms
We present a general decomposition algorithm that is uniformly applicable to every (suitably normalized) instance of Convex Quadratic Optimization and efficiently approaches an o...
Nikolas List, Hans-Ulrich Simon
MLDM
2009
Springer
15 years 4 months ago
The Needles-in-Haystack Problem
We consider a new data mining problem of detecting the members of a rare class of data, the needles, that have been hidden in a set of records, the haystack. Besides the haystack, ...
Katherine Moreland, Klaus Truemper