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» Intractability and clustering with constraints
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NIPS
2004
14 years 11 months ago
Expectation Consistent Free Energies for Approximate Inference
We propose a novel a framework for deriving approximations for intractable probabilistic models. This framework is based on a free energy (negative log marginal likelihood) and ca...
Manfred Opper, Ole Winther
ICML
2009
IEEE
15 years 10 months ago
Herding dynamical weights to learn
A new "herding" algorithm is proposed which directly converts observed moments into a sequence of pseudo-samples. The pseudosamples respect the moment constraints and ma...
Max Welling
BIBE
2007
IEEE
151views Bioinformatics» more  BIBE 2007»
14 years 11 months ago
On the Effectiveness of Constraints Sets in Clustering Genes
—In this paper, we have modified a constrained clustering algorithm to perform exploratory analysis on gene expression data using prior knowledge presented in the form of constr...
Erliang Zeng, Chengyong Yang, Tao Li, Giri Narasim...
KDD
2007
ACM
159views Data Mining» more  KDD 2007»
15 years 10 months ago
Constraint-driven clustering
Clustering methods can be either data-driven or need-driven. Data-driven methods intend to discover the true structure of the underlying data while need-driven methods aims at org...
Rong Ge, Martin Ester, Wen Jin, Ian Davidson
CASCON
1993
106views Education» more  CASCON 1993»
14 years 11 months ago
The use of process clustering in distributed-system event displays
When debugging a distributed application, a display showing the events causing interactions between processes can be very useful. If the number of processes is large, displaying a...
David J. Taylor