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行业发展研究 Context-Sensitive Semantic Smoothing for the Language Modeling Approach to Genomic IR(上下文敏感的语义平滑的语言建
Context-Sensitive Semantic Smoothing for the Language Modeling Approach to Genomic IR(上下文敏感的语义平滑的语言建模方法)
系统设计方案 measure through the cross-entropy of test data. In addition, we introduce two novel smoothing tech
measure through
the cross-entropy of test data. In addition,
we introduce two novel smoothing techniques,
one a variation of Jelinek-Mercer
smoothing and one a very simple linear interpolation
technique, both of which outperform
existing methods.
数值算法/人工智能 state of art language modeling methods: An Empirical Study of Smoothing Techniques for Language Mod
state of art language modeling methods:
An Empirical Study of Smoothing Techniques for Language Modeling.pdf
BLEU, a Method for Automatic Evaluation of Machine Translation.pdf
Class-based n-gram models of natural language.pdf
Distributed Language Modeling for N-best List Re-ranking.pdf
Distributed ...
行业发展研究 Author:Eubank year:(1999)Name:Nonparametric Regression and Spline Smoothing second edition
Author:Eubank year:(1999)Name:Nonparametric Regression and Spline Smoothing second edition
matlab例程 Interactive smoothing for your own data, with sliders to control derivative order, smooth width, a
Interactive smoothing for your own data, with sliders to control
derivative order, smooth width, and scale expansion.
matlab例程 Interactive smoothing for time-series signals, with sliders that allow you to adjust the smoothing
Interactive smoothing for time-series signals, with sliders that
allow you to adjust the smoothing parameters continuously
while observing the effect on your signal dynamically. Run
SmoothSliderTest to see how it works.
教育系统应用 SMOOTHING of images
SMOOTHING of images
matlab例程 Linera filtr (gaussian smoothing)
Linera filtr (gaussian smoothing)
文件格式 In this article, we present an overview of methods for sequential simulation from posterior distribu
In this article, we present an overview of methods for sequential simulation from posterior distributions.
These methods are of particular interest in Bayesian filtering for discrete time dynamic models
that are typically nonlinear and non-Gaussian. A general importance sampling framework is develop ...
Linux/Unix编程 srand[getpid[]] /* initialize some of the memory */ memset[heightmap, 0, MAPSIZE*MAPSIZE]
srand[getpid[]]
/* initialize some of the memory */
memset[heightmap, 0, MAPSIZE*MAPSIZE]
memset[vpage, 0, RENDERWIDTH * RENDERHEIGHT]
printf["Creating dx d fractal terrain\n", MAPSIZE, MAPSIZE]
heightmap[0] = [rand[] 128] + 64 // initialize starting point on map
CreateFract ...