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ICML
2008
IEEE
16 years 5 months ago
On the quantitative analysis of deep belief networks
Deep Belief Networks (DBN's) are generative models that contain many layers of hidden variables. Efficient greedy algorithms for learning and approximate inference have allow...
Ruslan Salakhutdinov, Iain Murray
128
Voted
KDD
2009
ACM
207views Data Mining» more  KDD 2009»
16 years 5 months ago
DynaMMo: mining and summarization of coevolving sequences with missing values
Given multiple time sequences with missing values, we propose DynaMMo which summarizes, compresses, and finds latent variables. The idea is to discover hidden variables and learn ...
Lei Li, James McCann, Nancy S. Pollard, Christos F...
ALT
2005
Springer
16 years 1 months ago
Teaching Learners with Restricted Mind Changes
Within learning theory teaching has been studied in various ways. In a common variant the teacher has to teach all learners that are restricted to output only consistent hypotheses...
Frank J. Balbach, Thomas Zeugmann
142
Voted
ALT
2004
Springer
16 years 1 months ago
New Revision Algorithms
A revision algorithm is a learning algorithm that identifies the target concept, starting from an initial concept. Such an algorithm is considered efficient if its complexity (in ...
Judy Goldsmith, Robert H. Sloan, Balázs Sz&...
GECCO
2009
Springer
15 years 11 months ago
On the scalability of XCS(F)
Many successful applications have proven the potential of Learning Classifier Systems and the XCS classifier system in particular in datamining, reinforcement learning, and func...
Patrick O. Stalph, Martin V. Butz, David E. Goldbe...