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IJCNN
2007
IEEE
13 years 11 months ago
Spectral Clustering of Synchronous Spike Trains
— In this paper a clustering algorithm that learns the groups of synchronized spike trains directly from data is proposed. Clustering of spike trains based on the presence of syn...
António R. C. Paiva, Sudhir Rao, Il Park, J...
ICRA
2007
IEEE
126views Robotics» more  ICRA 2007»
13 years 11 months ago
Incremental Spectral Clustering and Its Application To Topological Mapping
Abstract— This paper presents a novel use of spectral clustering algorithms to support cases where the entries in the affinity matrix are costly to compute. The method is increm...
Christoffer Valgren, Tom Duckett, Achim J. Lilient...
ICPR
2008
IEEE
13 years 11 months ago
Constrained clustering by a novel graph-based distance transformation
In this work we present a novel method to model instance-level constraints within a clustering algorithm. Thereby, both similarity and dissimilarity constraints can be used coeval...
Kai Rothaus, Xiaoyi Jiang
ICPR
2008
IEEE
13 years 11 months ago
A clustering algorithm combine the FCM algorithm with supervised learning normal mixture model
In this paper we propose a new clustering algorithm which combines the FCM clustering algorithm with the supervised learning normal mixture model; we call the algorithm as the FCM...
Wei Wang, Chunheng Wang, Xia Cui, Ai Wang
SIGIR
2009
ACM
13 years 11 months ago
Dynamicity vs. effectiveness: studying online clustering for scatter/gather
We proposed and implemented a novel clustering algorithm called LAIR2, which has constant running time average for on-the-fly Scatter/Gather browsing [4]. Our experiments showed ...
Weimao Ke, Cassidy R. Sugimoto, Javed Mostafa
WADS
2009
Springer
256views Algorithms» more  WADS 2009»
13 years 11 months ago
Dynamic Graph Clustering Using Minimum-Cut Trees
Abstract. Algorithms or target functions for graph clustering rarely admit quality guarantees or optimal results in general. Based on properties of minimum-cut trees, a clustering ...
Robert Görke, Tanja Hartmann, Dorothea Wagner
ICDM
2009
IEEE
165views Data Mining» more  ICDM 2009»
13 years 11 months ago
Cross-Guided Clustering: Transfer of Relevant Supervision across Domains for Improved Clustering
—Lack of supervision in clustering algorithms often leads to clusters that are not useful or interesting to human reviewers. We investigate if supervision can be automatically tr...
Indrajit Bhattacharya, Shantanu Godbole, Sachindra...
CIDM
2009
IEEE
13 years 11 months ago
Density-based clustering of polygons
– Clustering is an important task in spatial data mining and spatial analysis. We propose a clustering algorithm P-DBSCAN to cluster polygons in space. PDBSCAN is based on the we...
Deepti Joshi, Ashok Samal, Leen-Kiat Soh
CVPR
2010
IEEE
14 years 1 months ago
Clustering Dynamic Textures with the Hierarchical EM Algorithm
The dynamic texture (DT) is a probabilistic generative model, defined over space and time, that represents a video as the output of a linear dynamical system (LDS). The DT model ...
Antoni Chan, Emanuele Coviello, Gert Lanckriet
ICCAD
2007
IEEE
161views Hardware» more  ICCAD 2007»
14 years 1 months ago
Clustering based pruning for statistical criticality computation under process variations
— We present a new linear time technique to compute criticality information in a timing graph by dividing it into “zones”. Errors in using tightness probabilities for critica...
Hushrav Mogal, Haifeng Qian, Sachin S. Sapatnekar,...