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ISMB
1993
13 years 9 months ago
Discovering Sequence Similarity by the Algorithmic Significance Method
The minimal-length encoding approach is applied to define concept of sequence similarity. Asequence is defined to be similar to another sequence or to a set of keywords if it can ...
Aleksandar Milosavljevic
JPDC
2008
135views more  JPDC 2008»
13 years 7 months ago
Fast parallel GPU-sorting using a hybrid algorithm
This paper presents an algorithm for fast sorting of large lists using modern GPUs. The method achieves high speed by efficiently utilizing the parallelism of the GPU throughout th...
Erik Sintorn, Ulf Assarsson
KDD
2010
ACM
272views Data Mining» more  KDD 2010»
13 years 6 months ago
Scalable similarity search with optimized kernel hashing
Scalable similarity search is the core of many large scale learning or data mining applications. Recently, many research results demonstrate that one promising approach is creatin...
Junfeng He, Wei Liu, Shih-Fu Chang
CEC
2010
IEEE
13 years 9 months ago
Learning-assisted evolutionary search for scalable function optimization: LEM(ID3)
Inspired originally by the Learnable Evolution Model(LEM) [5], we investigate LEM(ID3), a hybrid of evolutionary search with ID3 decision tree learning. LEM(ID3) involves interleav...
Guleng Sheri, David Corne
SECON
2008
IEEE
14 years 2 months ago
SYNAPSE: A Network Reprogramming Protocol for Wireless Sensor Networks Using Fountain Codes
—Wireless reprogramming is a key functionality in Wireless Sensor Networks (WSNs). In fact, the requirements for the network may change in time, or new parameters might have to b...
Michele Rossi, Giovanni Zanca, Luca Stabellini, Ri...