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CORR
2004
Springer
140views Education» more  CORR 2004»
15 years 2 months ago
Integrating Defeasible Argumentation and Machine Learning Techniques
The field of machine learning (ML) is concerned with the question of how to construct algorithms that automatically improve with experience. In recent years many successful ML app...
Sergio Alejandro Gómez, Carlos Iván ...
135
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IJCAI
2007
15 years 4 months ago
Constructing New and Better Evaluation Measures for Machine Learning
Evaluation measures play an important role in machine learning because they are used not only to compare different learning algorithms, but also often as goals to optimize in cons...
Jin Huang, Charles X. Ling
APBC
2003
116views Bioinformatics» more  APBC 2003»
15 years 4 months ago
An Empirical Comparison of Supervised Machine Learning Techniques in Bioinformatics
Research in bioinformatics is driven by the experimental data. Current biological databases are populated by vast amounts of experimental data. Machine learning has been widely ap...
Aik Choon Tan, David Gilbert
JMLR
2010
192views more  JMLR 2010»
14 years 9 months ago
Efficient Learning of Deep Boltzmann Machines
We present a new approximate inference algorithm for Deep Boltzmann Machines (DBM's), a generative model with many layers of hidden variables. The algorithm learns a separate...
Ruslan Salakhutdinov, Hugo Larochelle
ACL
2010
15 years 20 days ago
Bucking the Trend: Large-Scale Cost-Focused Active Learning for Statistical Machine Translation
We explore how to improve machine translation systems by adding more translation data in situations where we already have substantial resources. The main challenge is how to buck ...
Michael Bloodgood, Chris Callison-Burch