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ECAI
2004
Springer
15 years 7 months ago
Learning Complex and Sparse Events in Long Sequences
The Hierarchical Hidden Markov Model (HHMM) is a well formalized tool suitable to model complex patterns in long temporal or spatial sequences. Even if effective algorithms are ava...
Marco Botta, Ugo Galassi, Attilio Giordana
JCP
2006
111views more  JCP 2006»
15 years 1 months ago
Mining Developing Trends of Dynamic Spatiotemporal Data Streams
This paper1 presents an efficient modeling technique for data streams in a dynamic spatiotemporal environment and its suitability for mining developing trends. The streaming data a...
Yu Meng, Margaret H. Dunham
ICASSP
2011
IEEE
14 years 5 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
104
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SOFTVIS
2005
ACM
15 years 7 months ago
Visualization of mobile object environments
This paper presents a system for visualizing mobile object frameworks. In such frameworks, the objects can migrate to remote hosts, along with their state and behavior, while the ...
Yaniv Frishman, Ayellet Tal
JSSPP
2001
Springer
15 years 6 months ago
Metrics for Parallel Job Scheduling and Their Convergence
The arrival process of jobs submitted to a parallel system is bursty, leading to fluctuations in the load at many time scales. In particular, rare events of extreme load may occu...
Dror G. Feitelson