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» Tackling Large State Spaces in Performance Modelling
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EMNLP
2007
15 years 2 months ago
Online Large-Margin Training for Statistical Machine Translation
We achieved a state of the art performance in statistical machine translation by using a large number of features with an online large-margin training algorithm. The millions of p...
Taro Watanabe, Jun Suzuki, Hajime Tsukada, Hideki ...
GECCO
2007
Springer
160views Optimization» more  GECCO 2007»
15 years 7 months ago
Quick-and-dirty ant colony optimization
Ant colony optimization (ACO) is a well known metaheuristic. In the literature it has been used for tackling many optimization problems. Often, ACO is hybridized with a local sear...
Paola Pellegrini, Elena Moretti
ACRI
2006
Springer
15 years 7 months ago
Optimal 6-State Algorithms for the Behavior of Several Moving Creatures
The goal of our investigation is to find automatically the absolutely best rule for a moving creature in a cellular field. The task of the creature is to visit all empty cells wi...
Mathias Halbach, Rolf Hoffmann, Lars Both
ICDE
2010
IEEE
222views Database» more  ICDE 2010»
14 years 12 months ago
Finding Clusters in subspaces of very large, multi-dimensional datasets
Abstract— We propose the Multi-resolution Correlation Cluster detection (MrCC), a novel, scalable method to detect correlation clusters able to analyze dimensional data in the ra...
Robson Leonardo Ferreira Cordeiro, Agma J. M. Trai...
TCS
2010
14 years 8 months ago
A fluid analysis framework for a Markovian process algebra
Markovian process algebras, such as PEPA and stochastic -calculus, bring a powerful compositional approach to the performance modelling of complex systems. However, the models gen...
Richard A. Hayden, Jeremy T. Bradley