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» Tackling Large State Spaces in Performance Modelling
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EMNLP
2007
13 years 10 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»
14 years 3 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
14 years 2 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»
13 years 7 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
13 years 3 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