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» A Genetic Algorithm for Clustering on Very Large Data Sets
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ICDE
2010
IEEE
273views Database» more  ICDE 2010»
14 years 7 months ago
WikiAnalytics: Ad-hoc Querying of Highly Heterogeneous Structured Data
Searching and extracting meaningful information out of highly heterogeneous datasets is a hot topic that received a lot of attention. However, the existing solutions are based on e...
Andrey Balmin, Emiran Curtmola
WAIM
2009
Springer
14 years 7 days ago
Kernel-Based Transductive Learning with Nearest Neighbors
In the k-nearest neighbor (KNN) classifier, nearest neighbors involve only labeled data. That makes it inappropriate for the data set that includes very few labeled data. In this ...
Liangcai Shu, Jinhui Wu, Lei Yu, Weiyi Meng
ICMLA
2010
13 years 5 months ago
Boosting Multi-Task Weak Learners with Applications to Textual and Social Data
Abstract--Learning multiple related tasks from data simultaneously can improve predictive performance relative to learning these tasks independently. In this paper we propose a nov...
Jean Baptiste Faddoul, Boris Chidlovskii, Fabien T...
RECOMB
2009
Springer
14 years 8 months ago
Spatial Clustering of Multivariate Genomic and Epigenomic Information
The combination of fully sequence genomes and new technologies for high density arrays and ultra-rapid sequencing enables the mapping of generegulatory and epigenetics marks on a g...
Rami Jaschek, Amos Tanay
NIPS
2008
13 years 9 months ago
Stochastic Relational Models for Large-scale Dyadic Data using MCMC
Stochastic relational models (SRMs) [15] provide a rich family of choices for learning and predicting dyadic data between two sets of entities. The models generalize matrix factor...
Shenghuo Zhu, Kai Yu, Yihong Gong