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» A Method for Dynamic Clustering of Data
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ICASSP
2011
IEEE
14 years 8 months ago
Joint modeling of observed inter-arrival times and waveform data with multiple hidden states for neural spike-sorting
We present a novel, maximum likelihood framework for automatic spike-sorting based on a joint statistical model of action potential waveform shape and inter-spike interval duratio...
Brett Matthews, Mark Clements
LCR
1998
Springer
137views System Software» more  LCR 1998»
15 years 8 months ago
Integrated Task and Data Parallel Support for Dynamic Applications
There is an emerging class of real-time interactive applications that require the dynamic integration of task and data parallelism. An example is the Smart Kiosk, a free-standing ...
James M. Rehg, Kathleen Knobe, Umakishore Ramachan...
KDD
2001
ACM
169views Data Mining» more  KDD 2001»
16 years 4 months ago
Hierarchical cluster analysis of SAGE data for cancer profiling
In this paper we present a method for clustering SAGE (Serial Analysis of Gene Expression) data to detect similarities and dissimilarities between different types of cancer on the...
Jörg Sander, Monica C. Sleumer, Raymond T. Ng
SDM
2012
SIAM
452views Data Mining» more  SDM 2012»
13 years 7 months ago
Density-based Projected Clustering over High Dimensional Data Streams
Clustering of high dimensional data streams is an important problem in many application domains, a prominent example being network monitoring. Several approaches have been lately ...
Irene Ntoutsi, Arthur Zimek, Themis Palpanas, Peer...
CIARP
2004
Springer
15 years 10 months ago
Parallel Algorithm for Extended Star Clustering
In this paper we present a new parallel clustering algorithm based on the extended star clustering method. This algorithm can be used for example to cluster massive data sets of do...
Reynaldo Gil-García, José Manuel Bad...