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» Using Random Forests in the Structured Language Model
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AAAI
1997
13 years 10 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
INLG
2010
Springer
13 years 6 months 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»
13 years 8 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»
13 years 8 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
ECIR
2004
Springer
13 years 10 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