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» Approximation Algorithms for Data Placement Problems
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IJCAI
1997
13 years 9 months ago
Extracting Propositions from Trained Neural Networks
This paper presents an algorithm for extract­ ing propositions from trained neural networks. The algorithm is a decompositional approach which can be applied to any neural networ...
Hiroshi Tsukimoto
ICDE
2007
IEEE
162views Database» more  ICDE 2007»
14 years 9 months ago
On Density Based Transforms for Uncertain Data Mining
In spite of the great progress in the data mining field in recent years, the problem of missing and uncertain data has remained a great challenge for data mining algorithms. Many ...
Charu C. Aggarwal
ISCC
2006
IEEE
123views Communications» more  ISCC 2006»
14 years 1 months ago
Similarity Search in a Hybrid Overlay P2P Network
P2P systems are increasingly used to discover and share various data between users. The performance of a P2P based information retrieval system is determined by the efficiency of...
Mouna Kacimi, Kokou Yétongnon
CGO
2011
IEEE
12 years 11 months ago
Language and compiler support for auto-tuning variable-accuracy algorithms
—Approximating ideal program outputs is a common technique for solving computationally difficult problems, for adhering to processing or timing constraints, and for performance ...
Jason Ansel, Yee Lok Wong, Cy P. Chan, Marek Olsze...
CORR
2007
Springer
128views Education» more  CORR 2007»
13 years 7 months ago
Model Selection Through Sparse Maximum Likelihood Estimation
We consider the problem of estimating the parameters of a Gaussian or binary distribution in such a way that the resulting undirected graphical model is sparse. Our approach is to...
Onureena Banerjee, Laurent El Ghaoui, Alexandre d'...