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ALT
1998
Springer
15 years 8 months ago
Predictive Learning Models for Concept Drift
Concept drift means that the concept about which data is obtained may shift from time to time, each time after some minimum permanence. Except for this minimum permanence, the con...
John Case, Sanjay Jain, Susanne Kaufmann, Arun Sha...
UAI
2000
15 years 5 months ago
Tractable Bayesian Learning of Tree Belief Networks
In this paper we present decomposable priors, a family of priors over structure and parameters of tree belief nets for which Bayesian learning with complete observations is tracta...
Marina Meila, Tommi Jaakkola
MEDES
2009
ACM
15 years 9 months ago
Web page ranking based on fuzzy and learning automata
The main goal of web pages ranking is to find the interrelated pages. In this paper, we introduce an algorithm called FPR-DLA. In the proposed method learning automata is assigned...
Zohreh Anari, Mohammad Reza Meybodi, Babak Anari
NIPS
2004
15 years 5 months ago
Learning Efficient Auditory Codes Using Spikes Predicts Cochlear Filters
The representation of acoustic signals at the cochlear nerve must serve a wide range of auditory tasks that require exquisite sensitivity in both time and frequency. Lewicki (2002...
Evan C. Smith, Michael S. Lewicki
CVPR
2010
IEEE
16 years 18 days ago
Learning Shift-Invariant Sparse Representation of Actions
A central problem in the analysis of motion capture (Mo- Cap) data is how to decompose motion sequences into primitives. Ideally, a description in terms of primitives should fac...
Yi Li