JMLR
2006
13 years 5 months ago
2006
This paper is about non-approximate acceleration of high-dimensional nonparametric operations such as k nearest neighbor classifiers. We attempt to exploit the fact that even if w...
IJDMB
2008
13 years 5 months ago
2008
: This paper addresses the sparse data problem in the linear regression model, namely the number of variables is significantly larger than the number of the data points for regress...
DATAMINE
2006
13 years 5 months ago
2006
Motivated by the poor performance (linear complexity) of the EM algorithm in clustering large data sets, and inspired by the successful accelerated versions of related algorithms l...
CLASSIFICATION
2008
13 years 5 months ago
2008
: We present a new iterative method for probabilistic clustering of data. Given clusters, their centers and the distances of data points from these centers, the probability of clus...
CAGD
2008
13 years 5 months ago
2008
A classic problem in geometric modelling is curve interpolation to data points. Some of the existing interpolation schemes only require point data, whereas others, require higher ...
ICML
2010
IEEE
13 years 5 months ago
2010
IEEE
In this paper we propose a novel clustering algorithm based on maximizing the mutual information between data points and clusters. Unlike previous methods, we neither assume the d...
ECAI
2010
Springer
13 years 6 months ago
2010
Springer
Large-scale text datasets have long eluded a family of particularly elegant and effective clustering methods that exploits the power of pair-wise similarities between data points ...
NIPS
2000
13 years 6 months ago
2000
We present a novel method for clustering using the support vector machine approach. Data points are mapped to a high dimensional feature space, where support vectors are used to d...
CATE
2004
13 years 6 months ago
2004
Recently web-based educational systems collect vast amounts of data on user patterns, and data mining methods can be applied to these databases to discover interesting associations...
AAAI
2006
13 years 6 months ago
2006
Learning application-specific distance metrics from labeled data is critical for both statistical classification and information retrieval. Most of the earlier work in this area h...