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CVPR
2000
IEEE
14 years 8 months ago
Learning in Gibbsian Fields: How Accurate and How Fast Can It Be?
?Gibbsian fields or Markov random fields are widely used in Bayesian image analysis, but learning Gibbs models is computationally expensive. The computational complexity is pronoun...
Song Chun Zhu, Xiuwen Liu
ICMI
2005
Springer
215views Biometrics» more  ICMI 2005»
13 years 12 months ago
Multimodal multispeaker probabilistic tracking in meetings
Tracking speakers in multiparty conversations constitutes a fundamental task for automatic meeting analysis. In this paper, we present a probabilistic approach to jointly track th...
Daniel Gatica-Perez, Guillaume Lathoud, Jean-Marc ...
DAC
2006
ACM
14 years 7 months ago
Criticality computation in parameterized statistical timing
Chips manufactured in 90 nm technology have shown large parametric variations, and a worsening trend is predicted. These parametric variations make circuit optimization difficult ...
Jinjun Xiong, Vladimir Zolotov, Natesan Venkateswa...
ICDE
2008
IEEE
135views Database» more  ICDE 2008»
14 years 7 months ago
Online Filtering, Smoothing and Probabilistic Modeling of Streaming data
In this paper, we address the problem of extending a relational database system to facilitate efficient real-time application of dynamic probabilistic models to streaming data. he ...
Bhargav Kanagal, Amol Deshpande
ISPD
2005
ACM
130views Hardware» more  ISPD 2005»
13 years 12 months ago
Improved algorithms for link-based non-tree clock networks for skew variability reduction
In the nanometer VLSI technology, the variation effects like manufacturing variation, power supply noise, temperature etc. become very significant. As one of the most vital nets...
Anand Rajaram, David Z. Pan, Jiang Hu