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FLAIRS
2008
13 years 7 months ago
Small Models of Large Machines
In this paper, we model large support vector machines (SVMs) by smaller networks in order to decrease the computational cost. The key idea is to generate additional training patte...
Pramod Lakshmi Narasimha, Sanjeev S. Malalur, Mich...
EMNLP
2007
13 years 6 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 ...
MDAFA
2004
Springer
114views Hardware» more  MDAFA 2004»
13 years 10 months ago
Modeling in the Large and Modeling in the Small
Abstract. As part of the AMMA project (ATLAS Model Management Architecture), we are currently building several model management tools to support the tasks of modeling in the large ...
Jean Bézivin, Frédéric Jouaul...
IANDC
2008
80views more  IANDC 2008»
13 years 4 months ago
Preemptive scheduling on a small number of hierarchical machines
We consider preemptive offline and online scheduling on identical machines and uniformly related machines in the hierarchical model, with the goal of minimizing the makespan. In t...
György Dósa, Leah Epstein
MLDM
2005
Springer
13 years 10 months ago
A Grouping Method for Categorical Attributes Having Very Large Number of Values
In supervised machine learning, the partitioning of the values (also called grouping) of a categorical attribute aims at constructing a new synthetic attribute which keeps the info...
Marc Boullé