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MCS
2000
Springer
15 years 11 months ago
Ensemble Methods in Machine Learning
Ensemble methods are learning algorithms that construct a set of classi ers and then classify new data points by taking a (weighted) vote of their predictions. The original ensembl...
Thomas G. Dietterich
AHS
2007
IEEE
208views Hardware» more  AHS 2007»
15 years 9 months ago
Evolving Redundant Structures for Reliable Circuits - Lessons Learned
Fault Tolerance is an increasing challenge for integrated circuits due to semiconductor technology scaling. This paper looks at how artificial evolution may be tuned to the creat...
Asbjørn Djupdal, Pauline C. Haddow
ICMLA
2007
15 years 8 months ago
Control of a re-entrant line manufacturing model with a reinforcement learning approach
This paper presents the application of a reinforcement learning (RL) approach for the near-optimal control of a re-entrant line manufacturing (RLM) model. The RL approach utilizes...
José A. Ramírez-Hernández, Em...
NAACL
2007
15 years 8 months ago
A Cascaded Machine Learning Approach to Interpreting Temporal Expressions
A new architecture for identifying and interpreting temporal expressions is introduced, in which the large set of complex hand-crafted rules standard in systems for this task is r...
David Ahn, Joris van Rantwijk, Maarten de Rijke
ACL
2004
15 years 8 months ago
Learning to Resolve Bridging References
We use machine learning techniques to find the best combination of local focus and lexical distance features for identifying the anchor of mereological bridging references. We fin...
Massimo Poesio, Rahul Mehta, Axel Maroudas, Janet ...