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DCC
2006
IEEE
14 years 9 months ago
Compression and Machine Learning: A New Perspective on Feature Space Vectors
The use of compression algorithms in machine learning tasks such as clustering and classification has appeared in a variety of fields, sometimes with the promise of reducing probl...
D. Sculley, Carla E. Brodley
SAT
2009
Springer
111views Hardware» more  SAT 2009»
14 years 4 months ago
Restart Strategy Selection Using Machine Learning Techniques
Abstract. Restart strategies are an important factor in the performance of conflict-driven Davis Putnam style SAT solvers. Selecting a good restart strategy for a problem instance...
Shai Haim, Toby Walsh
ICML
2000
IEEE
14 years 10 months ago
Correlation-based Feature Selection for Discrete and Numeric Class Machine Learning
Algorithms for feature selection fall into two broad categories: wrappers that use the learning algorithm itself to evaluate the usefulness of features and filters that evaluate f...
Mark A. Hall
NECO
2010
136views more  NECO 2010»
13 years 8 months ago
Learning to Represent Spatial Transformations with Factored Higher-Order Boltzmann Machines
To allow the hidden units of a restricted Boltzmann machine to model the transformation between two successive images, Memisevic and Hinton (2007) introduced three-way multiplicat...
Roland Memisevic, Geoffrey E. Hinton
ICONIP
2008
13 years 11 months ago
Experimental Study of Ergodic Learning Curve in Hidden Markov Models
A number of learning machines used in information science are not regular, but rather singular, because they are non-identifiable and their Fisher information matrices are singula...
Masashi Matsumoto, Sumio Watanabe