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ICMLA
2007
15 years 8 months ago
Maximum Likelihood Quantization of Genomic Features Using Dynamic Programming
Dynamic programming is introduced to quantize a continuous random variable into a discrete random variable. Quantization is often useful before statistical analysis or reconstruct...
Mingzhou (Joe) Song, Robert M. Haralick, Sté...
NAACL
2007
15 years 8 months ago
Are Very Large N-Best Lists Useful for SMT?
This paper describes an efficient method to extract large n-best lists from a word graph produced by a statistical machine translation system. The extraction is based on the k sh...
Sasa Hasan, Richard Zens, Hermann Ney
KDD
2006
ACM
156views Data Mining» more  KDD 2006»
16 years 7 months ago
Discovering significant OPSM subspace clusters in massive gene expression data
Order-preserving submatrixes (OPSMs) have been accepted as a biologically meaningful subspace cluster model, capturing the general tendency of gene expressions across a subset of ...
Byron J. Gao, Obi L. Griffith, Martin Ester, Steve...
ISPDC
2008
IEEE
16 years 1 months ago
Performance Analysis of Grid DAG Scheduling Algorithms using MONARC Simulation Tool
This paper presents a new approach for analyzing the performance of grid scheduling algorithms for tasks with dependencies. Finding the optimal procedures for DAG scheduling in Gr...
Florin Pop, Ciprian Dobre, Valentin Cristea
CIARP
2006
Springer
15 years 8 months ago
Robustness Analysis of the Neural Gas Learning Algorithm
The Neural Gas (NG) is a Vector Quantization technique where a set of prototypes self organize to represent the topology structure of the data. The learning algorithm of the Neural...
Carolina Saavedra, Sebastián Moreno, Rodrig...