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ACL
2006
15 years 8 months ago
Approximation Lasso Methods for Language Modeling
Lasso is a regularization method for parameter estimation in linear models. It optimizes the model parameters with respect to a loss function subject to model complexities. This p...
Jianfeng Gao, Hisami Suzuki, Bin Yu
EUSFLAT
2003
120views Fuzzy Logic» more  EUSFLAT 2003»
15 years 8 months ago
A Type 2 fuzzy system modelling algorithm
In this paper, a modified fuzzy system modelling algorithm that incorporates Type 2 fuzzy sets, which is based on intervalvalued membership degrees rather than singleton membershi...
Kemal Kilic, Özge Uncu, I. Burhan Türkse...
WSC
1997
15 years 8 months ago
Modeling Dependencies in Stochastic Simulation Inputs
We discuss some basic techniques for modeling dependence between the random variables that are inputs to a simulation model, with the main emphasis being continuous bivariate dist...
James R. Wilson
CSC
2010
15 years 1 months ago
Performance Modeling, Analysis, and Optimization of Cell-List Based Molecular Dynamics
- We have developed a performance prediction model for non-bonded interaction computations in molecular dynamics simulations, thereby predicting the optimal cell dimension in a lin...
Manaschai Kunaseth, Rajiv K. Kalia, Aiichiro Nakan...
JMLR
2010
107views more  JMLR 2010»
15 years 1 months ago
Learning Instance-Specific Predictive Models
This paper introduces a Bayesian algorithm for constructing predictive models from data that are optimized to predict a target variable well for a particular instance. This algori...
Shyam Visweswaran, Gregory F. Cooper