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» Computational Experience with the Batch Means Method
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JSW
2007
126views more  JSW 2007»
14 years 11 months ago
On Remote and Virtual Experiments in eLearning
— The science of physics is based on theories and models as well as experiments: the former structure relations and simplify reality to a degree such that predictions on physical...
Sabina Jeschke, Harald Scheel, Thomas Richter, Chr...
ML
2008
ACM
14 years 11 months ago
Margin-based first-order rule learning
Abstract We present a new margin-based approach to first-order rule learning. The approach addresses many of the prominent challenges in first-order rule learning, such as the comp...
Ulrich Rückert, Stefan Kramer
CCGRID
2005
IEEE
15 years 5 months ago
Dynamic load balancing experiments in a grid
Connected world-widely distributed computers and data systems establish a global source of processing power and data, called a grid. Key properties of a grid are the fact that com...
Menno Dobber, Ger Koole, Robert D. van der Mei
JMLR
2008
230views more  JMLR 2008»
14 years 11 months ago
Exponentiated Gradient Algorithms for Conditional Random Fields and Max-Margin Markov Networks
Log-linear and maximum-margin models are two commonly-used methods in supervised machine learning, and are frequently used in structured prediction problems. Efficient learning of...
Michael Collins, Amir Globerson, Terry Koo, Xavier...
ICDM
2002
IEEE
105views Data Mining» more  ICDM 2002»
15 years 4 months ago
Empirical Comparison of Various Reinforcement Learning Strategies for Sequential Targeted Marketing
We empirically evaluate the performance of various reinforcement learning methods in applications to sequential targeted marketing. In particular, we propose and evaluate a progre...
Naoki Abe, Edwin P. D. Pednault, Haixun Wang, Bian...