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» Density Estimation in Linear Time
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ICML
2009
IEEE
14 years 11 months ago
A stochastic memoizer for sequence data
We propose an unbounded-depth, hierarchical, Bayesian nonparametric model for discrete sequence data. This model can be estimated from a single training sequence, yet shares stati...
Frank Wood, Cédric Archambeau, Jan Gasthaus...
STOC
2001
ACM
134views Algorithms» more  STOC 2001»
14 years 10 months ago
Data-streams and histograms
Histograms are typically used to approximate data distributions. Histograms and related synopsis structures have been successful in a wide variety of popular database applications...
Sudipto Guha, Nick Koudas, Kyuseok Shim
ICCAD
2004
IEEE
145views Hardware» more  ICCAD 2004»
14 years 7 months ago
Asymptotic probability extraction for non-normal distributions of circuit performance
While process variations are becoming more significant with each new IC technology generation, they are often modeled via linear regression models so that the resulting performanc...
Xin Li, Jiayong Le, Padmini Gopalakrishnan, Lawren...
DSN
2009
IEEE
14 years 4 months ago
MAP-AMVA: Approximate mean value analysis of bursty systems
MAP queueing networks are recently proposed models for performance assessment of enterprise systems, such as multi-tier applications, where workloads are significantly affected b...
Giuliano Casale, Evgenia Smirni
ACCV
2009
Springer
14 years 4 months ago
An Online Framework for Learning Novel Concepts over Multiple Cues
Abstract. We propose an online learning algorithm to tackle the problem of learning under limited computational resources in a teacher-student scenario, over multiple visual cues. ...
Luo Jie, Francesco Orabona, Barbara Caputo