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» Maximum likelihood analysis of algorithms and data structure...
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KDD
2009
ACM
191views Data Mining» more  KDD 2009»
14 years 8 months ago
Scalable pseudo-likelihood estimation in hybrid random fields
Learning probabilistic graphical models from high-dimensional datasets is a computationally challenging task. In many interesting applications, the domain dimensionality is such a...
Antonino Freno, Edmondo Trentin, Marco Gori
KDD
2009
ACM
364views Data Mining» more  KDD 2009»
14 years 8 months ago
Causality quantification and its applications: structuring and modeling of multivariate time series
Time series prediction is an important issue in a wide range of areas. There are various real world processes whose states vary continuously, and those processes may have influenc...
Takashi Shibuya, Tatsuya Harada, Yasuo Kuniyoshi
CVPR
2008
IEEE
14 years 10 months ago
Max Margin AND/OR Graph learning for parsing the human body
We present a novel structure learning method, Max Margin AND/OR Graph (MM-AOG), for parsing the human body into parts and recovering their poses. Our method represents the human b...
Long Zhu, Yuanhao Chen, Yifei Lu, Chenxi Lin, Alan...
VISUALIZATION
2005
IEEE
14 years 1 months ago
Query-Driven Visualization of Large Data Sets
We present a practical and general-purpose approach to large and complex visual data analysis where visualization processing, rendering and subsequent human interpretation is cons...
Kurt Stockinger, John Shalf, Kesheng Wu, E. Wes Be...
IPPS
2000
IEEE
14 years 17 days ago
PaDDMAS: Parallel and Distributed Data Mining Application Suite
Discovering complex associations, anomalies and patterns in distributed data sets is gaining popularity in a range of scientific, medical and business applications. Various algor...
Omer F. Rana, David W. Walker, Maozhen Li, Steven ...