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» A fast algorithm for computing large Fibonacci numbers
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JCP
2008
171views more  JCP 2008»
15 years 3 months ago
Mining Frequent Subgraph by Incidence Matrix Normalization
Existing frequent subgraph mining algorithms can operate efficiently on graphs that are sparse, have vertices with low and bounded degrees, and contain welllabeled vertices and edg...
Jia Wu, Ling Chen
122
Voted
JCT
2007
117views more  JCT 2007»
15 years 3 months ago
Large independent sets in regular graphs of large girth
Let G be a d-regular graph with girth g, and let α be the independence number of G. We show that α(G) ≥ 1 2 1 − (d − 1)−2/(d−2) − (g) n where (g) → 0 as g → ∞,...
Joseph Lauer, Nicholas C. Wormald
ESANN
2006
15 years 4 months ago
An algorithm for fast and reliable ESOM learning
The training of Emergent Self-organizing Maps (ESOM ) with large datasets can be a computationally demanding task. Batch learning may be used to speed up training. It is demonstrat...
Mario Nöcker, Fabian Mörchen, Alfred Ult...
158
Voted
ICMLA
2003
15 years 4 months ago
Fast Class-Attribute Interdependence Maximization (CAIM) Discretization Algorithm
– Discretization is a process of converting a continuous attribute into an attribute that contains small number of distinct values. One of the major reasons for discretizing an a...
Lukasz A. Kurgan, Krzysztof J. Cios
175
Voted
ECCV
2010
Springer
15 years 8 months ago
Fast Approximate Nearest Neighbor Methods for Non-Euclidean Manifolds with Applications to Human Activity Analysis in Videos
Approximate Nearest Neighbor (ANN) methods such as Locality Sensitive Hashing, Semantic Hashing, and Spectral Hashing, provide computationally ecient procedures for nding objects...
Rizwan Chaudhry, Yuri Ivanov