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ACL
2006
13 years 11 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
GECCO
2008
Springer
146views Optimization» more  GECCO 2008»
13 years 10 months ago
A formal performance modeling framework for bio-inspired ad hoc routing protocols
Bio-inspired ad hoc routing is an active area of research. The designers of these algorithms predominantly evaluate the performance of their protocols with the help of simulation ...
Muhammad Saleem, Syed Ali Khayam, Muddassar Farooq
SDM
2008
SIAM
138views Data Mining» more  SDM 2008»
13 years 11 months ago
Learning Markov Network Structure using Few Independence Tests
In this paper we present the Dynamic Grow-Shrink Inference-based Markov network learning algorithm (abbreviated DGSIMN), which improves on GSIMN, the state-ofthe-art algorithm for...
Parichey Gandhi, Facundo Bromberg, Dimitris Margar...
GECCO
2005
Springer
134views Optimization» more  GECCO 2005»
14 years 3 months ago
Predicting mining activity with parallel genetic algorithms
We explore several different techniques in our quest to improve the overall model performance of a genetic algorithm calibrated probabilistic cellular automata. We use the Kappa ...
Sam Talaie, Ryan E. Leigh, Sushil J. Louis, Gary L...
IPSN
2003
Springer
14 years 2 months ago
Hypothesis Testing over Factorizations for Data Association
Abstract. The issue of data association arises frequently in sensor networks; whenever multiple sensors and sources are present, it may be necessary to determine which observations...
Alexander T. Ihler, John W. Fisher III, Alan S. Wi...