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» Structure learning of Bayesian networks using constraints
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158
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HYBRID
1998
Springer
15 years 9 months ago
High Order Eigentensors as Symbolic Rules in Competitive Learning
We discuss properties of high order neurons in competitive learning. In such neurons, geometric shapes replace the role of classic `point' neurons in neural networks. Complex ...
Hod Lipson, Hava T. Siegelmann
SECON
2008
IEEE
15 years 11 months ago
Practical Algorithms for Gathering Stored Correlated Data in a Network
—Many sensing systems remotely monitor/measure an environment at several sites, and then report these observations to a central site. We propose and investigate several practical...
Ramin Khalili, James F. Kurose
KDD
2006
ACM
191views Data Mining» more  KDD 2006»
16 years 5 months ago
Beyond classification and ranking: constrained optimization of the ROI
Classification has been commonly used in many data mining projects in the financial service industry. For instance, to predict collectability of accounts receivable, a binary clas...
Lian Yan, Patrick Baldasare
130
Voted
CORR
2006
Springer
143views Education» more  CORR 2006»
15 years 5 months ago
Revealing the Autonomous System Taxonomy: The Machine Learning Approach
Although the Internet AS-level topology has been extensively studied over the past few years, little is known about the details of the AS taxonomy. An AS "node" can repre...
Xenofontas A. Dimitropoulos, Dmitri V. Krioukov, G...
NOCS
2009
IEEE
15 years 11 months ago
Scalability of network-on-chip communication architecture for 3-D meshes
Design Constraints imposed by global interconnect delays as well as limitations in integration of disparate technologies make 3-D chip stacks an enticing technology solution for m...
Awet Yemane Weldezion, Matt Grange, Dinesh Pamunuw...