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» Learning Behavior Models for Hybrid Timed Systems
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157
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ICML
2010
IEEE
15 years 4 months ago
Continuous-Time Belief Propagation
Many temporal processes can be naturally modeled as a stochastic system that evolves continuously over time. The representation language of continuous-time Bayesian networks allow...
Tal El-Hay, Ido Cohn, Nir Friedman, Raz Kupferman
156
Voted
MIR
2005
ACM
129views Multimedia» more  MIR 2005»
15 years 9 months ago
Tracking concept drifting with an online-optimized incremental learning framework
Concept drifting is an important and challenging research issue in the field of machine learning. This paper mainly addresses the issue of semantic concept drifting in time series...
Jun Wu, Dayong Ding, Xian-Sheng Hua, Bo Zhang
LISA
2007
15 years 5 months ago
NetADHICT: A Tool for Understanding Network Traffic
Computer and network administrators are often confused or uncertain about the behavior of their networks. Traditional analysis using IP ports, addresses, and protocols are insuffi...
Hajime Inoue, Dana Jansens, Abdulrahman Hijazi, An...
KDD
2008
ACM
186views Data Mining» more  KDD 2008»
16 years 4 months ago
Cut-and-stitch: efficient parallel learning of linear dynamical systems on smps
Multi-core processors with ever increasing number of cores per chip are becoming prevalent in modern parallel computing. Our goal is to make use of the multi-core as well as multi...
Lei Li, Wenjie Fu, Fan Guo, Todd C. Mowry, Christo...
125
Voted
IEICET
2006
114views more  IEICET 2006»
15 years 3 months ago
Synchronization Verification in System-Level Design with ILP Solvers
Concurrency is one of the most important issues in system-level design. Interleaving among parallel processes can cause an extremely large number of different behaviors, making de...
Thanyapat Sakunkonchak, Satoshi Komatsu, Masahiro ...