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» Machine learning problems from optimization perspective
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JMLR
2012
13 years 6 months ago
Marginal Regression For Multitask Learning
Variable selection is an important and practical problem that arises in analysis of many high-dimensional datasets. Convex optimization procedures that arise from relaxing the NP-...
Mladen Kolar, Han Liu
259
Voted
ICDAR
2011
IEEE
14 years 3 months ago
Text Detection and Character Recognition in Scene Images with Unsupervised Feature Learning
—Reading text from photographs is a challenging problem that has received a signicant amount of attention. Two key components of most systems are (i) text detection from images a...
Adam Coates, Blake Carpenter, Carl Case, Sanjeev S...
115
Voted
TNN
2008
181views more  TNN 2008»
15 years 3 months ago
Optimized Approximation Algorithm in Neural Networks Without Overfitting
In this paper, an optimized approximation algorithm (OAA) is proposed to address the overfitting problem in function approximation using neural networks (NNs). The optimized approx...
Yinyin Liu, Janusz A. Starzyk, Zhen Zhu
159
Voted
SEMWEB
2010
Springer
15 years 1 months ago
Optimize First, Buy Later: Analyzing Metrics to Ramp-Up Very Large Knowledge Bases
As knowledge bases move into the landscape of larger ontologies and have terabytes of related data, we must work on optimizing the performance of our tools. We are easily tempted t...
Paea LePendu, Natalya Fridman Noy, Clement Jonquet...
ICML
1996
IEEE
16 years 4 months ago
Passive Distance Learning for Robot Navigation
Autonomous mobile robots need good models of their environment, sensors and actuators to navigate reliably and efficiently. While this information can be supplied by humans, or le...
Sven Koenig, Reid G. Simmons