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VISUALIZATION
1995
IEEE
14 years 2 months ago
Recursive Pattern: A Technique for Visualizing Very Large Amounts of Data
Animportantgoalofvisualizationtechnologyistosupport the exploration and analysis of very large amounts of data. In this paper, we propose a new visualization technique called ‘r...
Daniel A. Keim, Mihael Ankerst, Hans-Peter Kriegel
KDD
1997
ACM
154views Data Mining» more  KDD 1997»
14 years 2 months ago
Autonomous Discovery of Reliable Exception Rules
This paper presents an autonomous algorithm for discovering exception rules from data sets. An exception rule, which is defined as a deviational pattern to a well-known fact, exhi...
Einoshin Suzuki
ICPR
2010
IEEE
14 years 2 months ago
Learning a Joint Manifold Representation from Multiple Data Sets
—The problem we address in the paper is how to learn a joint representation from data lying on multiple manifolds. We are given multiple data sets and there is an underlying comm...
Marwan Torki, Ahmed Elgammal, Chan-Su Lee
KDD
2000
ACM
153views Data Mining» more  KDD 2000»
14 years 2 months ago
The generalized Bayesian committee machine
In this paper we introduce the Generalized Bayesian Committee Machine (GBCM) for applications with large data sets. In particular, the GBCM can be used in the context of kernel ba...
Volker Tresp
KDD
2000
ACM
142views Data Mining» more  KDD 2000»
14 years 2 months ago
Automating exploratory data analysis for efficient data mining
Having access to large data sets for the purpose of predictive data mining does not guarantee good models, even when the size of the training data is virtually unlimited. Instead,...
Jonathan D. Becher, Pavel Berkhin, Edmund Freeman
ALT
2000
Springer
14 years 2 months ago
Computationally Efficient Transductive Machines
In this paper1 we propose a new algorithm for providing confidence and credibility values for predictions on a multi-class pattern recognition problem which uses Support Vector mac...
Craig Saunders, Alexander Gammerman, Volodya Vovk
EDBTW
2006
Springer
14 years 2 months ago
Constructing Optimal Wavelet Synopses
The wavelet decomposition is a proven tool for constructing concise synopses of massive data sets and rapid changing data streams, which can be used to obtain fast approximate, wit...
Dimitris Sacharidis
ECML
2006
Springer
14 years 2 months ago
Why Is Rule Learning Optimistic and How to Correct It
Abstract. In their search through a huge space of possible hypotheses, rule induction algorithms compare estimations of qualities of a large number of rules to find the one that ap...
Martin Mozina, Janez Demsar, Jure Zabkar, Ivan Bra...
CVPR
2006
IEEE
14 years 2 months ago
Region-based Image Annotation using Asymmetrical Support Vector Machine-based Multiple-Instance Learning
In region-based image annotation, keywords are usually associated with images instead of individual regions in the training data set. This poses a major challenge for any learning...
Changbo Yang, Ming Dong, Jing Hua
FGR
2004
IEEE
133views Biometrics» more  FGR 2004»
14 years 2 months ago
Finding Temporal Patterns by Data Decomposition
We present a new unsupervised learning technique for the discovery of temporal clusters in large data sets. Our method performs hierarchical decomposition of the data to find stru...
David C. Minnen, Christopher Richard Wren