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» Unifying Probability with Nondeterminism
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ICML
2005
IEEE
14 years 8 months ago
A new Mallows distance based metric for comparing clusterings
Despite of the large number of algorithms developed for clustering, the study on comparing clustering results is limited. In this paper, we propose a measure for comparing cluster...
Ding Zhou, Jia Li, Hongyuan Zha
DCC
2006
IEEE
14 years 7 months ago
Joint Source-Channel Decoding of Multiple Description Quantized Markov Sequences
This paper proposes a framework for joint source-channel decoding of Markov sequences that are coded by a fixed-rate multiple description quantizer (MDQ), and transmitted via a lo...
Xiaolin Wu, Xiaohan Wang
ICDM
2007
IEEE
122views Data Mining» more  ICDM 2007»
14 years 1 months ago
Representing Tuple and Attribute Uncertainty in Probabilistic Databases
There has been a recent surge in work in probabilistic databases, propelled in large part by the huge increase in noisy data sources — sensor data, experimental data, data from ...
Prithviraj Sen, Amol Deshpande, Lise Getoor
AAAI
2008
13 years 10 months ago
Lifted First-Order Belief Propagation
Unifying first-order logic and probability is a long-standing goal of AI, and in recent years many representations combining aspects of the two have been proposed. However, infere...
Parag Singla, Pedro Domingos
COLT
2008
Springer
13 years 9 months ago
Model Selection and Stability in k-means Clustering
Clustering Stability methods are a family of widely used model selection techniques applied in data clustering. Their unifying theme is that an appropriate model should result in ...
Ohad Shamir, Naftali Tishby