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» Learning from Highly Structured Data by Decomposition
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82
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IJAR
2006
89views more  IJAR 2006»
14 years 10 months ago
Learning probabilistic decision graphs
Probabilistic decision graphs (PDGs) are a representation language for probability distributions based on binary decision diagrams. PDGs can encode (context-specific) independence...
Manfred Jaeger, Jens D. Nielsen, Tomi Silander
EMNLP
2007
14 years 11 months ago
Finding Good Sequential Model Structures using Output Transformations
In Sequential Viterbi Models, such as HMMs, MEMMs, and Linear Chain CRFs, the type of patterns over output sequences that can be learned by the model depend directly on the modelā...
Edward Loper
PAM
2007
Springer
15 years 4 months ago
Neuro-fuzzy Processing of Packet Dispersion Traces for Highly Variable Cross-Traffic Estimation
Cross-traffic data rate over the tight link of a path can be estimated using different active probing packet dispersion techniques. Many of these techniques send large amounts of p...
Marco A. Alzate, Néstor M. Peña, Mig...
79
Voted
ICDM
2003
IEEE
154views Data Mining» more  ICDM 2003»
15 years 3 months ago
Frequent Sub-Structure-Based Approaches for Classifying Chemical Compounds
In this paper we study the problem of classifying chemical compound datasets. We present a sub-structure-based classification algorithm that decouples the sub-structure discovery...
Mukund Deshpande, Michihiro Kuramochi, George Kary...
101
Voted
ICC
2007
IEEE
137views Communications» more  ICC 2007»
15 years 4 months ago
A Novel Algorithm and Architecture for High Speed Pattern Matching in Resource-Limited Silicon Solution
— Network Intrusion Detection Systems (NIDS) are more and more important for identifying and preventing the malicious attacks over the network. This paper proposes a novel cost-e...
Nen-Fu Huang, Yen-Ming Chu, Chi-Hung Tsai, Chen-Yi...