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» Learning Patterns in Noisy Data: The AQ Approach
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DCG
2008
104views more  DCG 2008»
15 years 4 months ago
Finding the Homology of Submanifolds with High Confidence from Random Samples
Recently there has been a lot of interest in geometrically motivated approaches to data analysis in high dimensional spaces. We consider the case where data is drawn from sampling...
Partha Niyogi, Stephen Smale, Shmuel Weinberger
136
Voted
KDD
2003
ACM
135views Data Mining» more  KDD 2003»
16 years 5 months ago
Efficiently handling feature redundancy in high-dimensional data
High-dimensional data poses a severe challenge for data mining. Feature selection is a frequently used technique in preprocessing high-dimensional data for successful data mining....
Lei Yu, Huan Liu
COLT
1999
Springer
15 years 9 months ago
On a Generalized Notion of Mistake Bounds
This paper proposes the use of constructive ordinals as mistake bounds in the on-line learning model. This approach elegantly generalizes the applicability of the on-line mistake ...
Sanjay Jain, Arun Sharma
IDEAL
2009
Springer
15 years 2 months ago
Implementation and Integration of Algorithms into the KEEL Data-Mining Software Tool
This work is related to the KEEL1 (Knowledge Extraction based on Evolutionary Learning) tool, a non-commercial software that supports data management, design of experiments and an ...
Alberto Fernández, Julián Luengo, Jo...
CVPR
2010
IEEE
16 years 1 months ago
Improving State-of-the-Art OCR through High-Precision Document-Specific Modeling
Optical character recognition (OCR) remains a difficult problem for noisy documents or documents not scanned at high resolution. Many current approaches rely on stored font models...
Andrew Kae, Gary Huang, Erik Learned-miller, Carl ...