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ICML
2005
IEEE
14 years 8 months ago
Learning from labeled and unlabeled data on a directed graph
We propose a general framework for learning from labeled and unlabeled data on a directed graph in which the structure of the graph including the directionality of the edges is co...
Bernhard Schölkopf, Dengyong Zhou, Jiayuan Hu...
BMCBI
2011
12 years 11 months ago
ShoRAH: estimating the genetic diversity of a mixed sample from next-generation sequencing data
Background: With next-generation sequencing technologies, experiments that were considered prohibitive only a few years ago are now possible. However, while these technologies hav...
Osvaldo Zagordi, Arnab Bhattacharya, Nicholas Erik...
ICTAI
1997
IEEE
13 years 11 months ago
Exploiting Symbolic Techniques within Genetic Algorithms for Power Optimization
This paper proposes an optimization algorithm for reducing the power dissipation in a sequential circuit. The encoding of the different states in a Finite State Machine is modifie...
S. Chuisano, Fulvio Corno, Paolo Prinetto, Maurizi...
ICDM
2005
IEEE
189views Data Mining» more  ICDM 2005»
14 years 1 months ago
Integrating Hidden Markov Models and Spectral Analysis for Sensory Time Series Clustering
We present a novel approach for clustering sequences of multi-dimensional trajectory data obtained from a sensor network. The sensory time-series data present new challenges to da...
Jie Yin, Qiang Yang
KDD
2012
ACM
281views Data Mining» more  KDD 2012»
11 years 9 months ago
Active spectral clustering via iterative uncertainty reduction
Spectral clustering is a widely used method for organizing data that only relies on pairwise similarity measurements. This makes its application to non-vectorial data straightforw...
Fabian L. Wauthier, Nebojsa Jojic, Michael I. Jord...