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» Using Random Forests in the Structured Language Model
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109
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AAAI
1997
15 years 3 months ago
Effective Bayesian Inference for Stochastic Programs
In this paper, we propose a stochastic version of a general purpose functional programming language as a method of modeling stochastic processes. The language contains random choi...
Daphne Koller, David A. McAllester, Avi Pfeffer
113
Voted
INLG
2010
Springer
15 years 10 days ago
Named Entity Generation Using Sampling-based Structured Prediction
The problem of Named Entity Generation is expressed as a conditional probability model over a structured domain. By defining a factor-graph model over the mentions of a text, we o...
Guillaume Bouchard
CVIU
2007
113views more  CVIU 2007»
15 years 2 months ago
Primal sketch: Integrating structure and texture
This article proposes a generative image model, which is called ‘‘primal sketch,’’ following Marr’s insight and terminology. This model combines two prominent classes of...
Cheng-en Guo, Song Chun Zhu, Ying Nian Wu
CORR
2010
Springer
182views Education» more  CORR 2010»
15 years 2 months ago
SPOT: An R Package For Automatic and Interactive Tuning of Optimization Algorithms by Sequential Parameter Optimization
The sequential parameter optimization (spot) package for R (R Development Core Team, 2008) is a toolbox for tuning and understanding simulation and optimization algorithms. Model-...
Thomas Bartz-Beielstein
100
Voted
ECIR
2004
Springer
15 years 3 months ago
Applying the Divergence from Randomness Approach for Content-Only Search in XML Documents
Content-only retrieval of XML documents deals with the problem of locating the smallest XML elements that satisfy the query. In this paper, we investigate the application of a spec...
Mohammad Abolhassani, Norbert Fuhr