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SETN
2004
Springer
15 years 7 months ago
Incremental Mixture Learning for Clustering Discrete Data
Abstract. This paper elaborates on an efficient approach for clustering discrete data by incrementally building multinomial mixture models through likelihood maximization using the...
Konstantinos Blekas, Aristidis Likas
ICMCS
2006
IEEE
111views Multimedia» more  ICMCS 2006»
15 years 7 months ago
Probabilistic Multimodality Fusion for Event based Home Photo Clustering
This paper presents a novel probabilistic approach to fusing multimodal metadata for event based home photo clustering. Photo events are characterized by the coherence of multimod...
Tao Mei, Bin Wang, Xian-Sheng Hua, He-Qin Zhou, Sh...
CSB
2004
IEEE
136views Bioinformatics» more  CSB 2004»
15 years 5 months ago
Minimum Entropy Clustering and Applications to Gene Expression Analysis
Clustering is a common methodology for analyzing the gene expression data. In this paper, we present a new clustering algorithm from an information-theoretic point of view. First,...
Haifeng Li, Keshu Zhang, Tao Jiang
KDD
2008
ACM
244views Data Mining» more  KDD 2008»
16 years 2 months ago
Probabilistic latent semantic visualization: topic model for visualizing documents
We propose a visualization method based on a topic model for discrete data such as documents. Unlike conventional visualization methods based on pairwise distances such as multi-d...
Tomoharu Iwata, Takeshi Yamada, Naonori Ueda
KDD
2002
ACM
118views Data Mining» more  KDD 2002»
16 years 2 months ago
SECRET: a scalable linear regression tree algorithm
Recently there has been an increasing interest in developing regression models for large datasets that are both accurate and easy to interpret. Regressors that have these properti...
Alin Dobra, Johannes Gehrke