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» Sequential predictions based on algorithmic complexity
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KDD
2002
ACM
171views Data Mining» more  KDD 2002»
14 years 5 months ago
Mining complex models from arbitrarily large databases in constant time
In this paper we propose a scaling-up method that is applicable to essentially any induction algorithm based on discrete search. The result of applying the method to an algorithm ...
Geoff Hulten, Pedro Domingos
VLSID
1997
IEEE
135views VLSI» more  VLSID 1997»
13 years 9 months ago
Parallel Genetic Algorithms for Simulation-Based Sequential Circuit Test Generation
The problem of test generation belongs to the class of NP-complete problems and it is becoming more and more di cult as the complexity of VLSI circuits increases, and as long as e...
Dilip Krishnaswamy, Michael S. Hsiao, Vikram Saxen...
JMLR
2006
90views more  JMLR 2006»
13 years 5 months ago
Superior Guarantees for Sequential Prediction and Lossless Compression via Alphabet Decomposition
We present worst case bounds for the learning rate of a known prediction method that is based on hierarchical applications of binary context tree weighting (CTW) predictors. A heu...
Ron Begleiter, Ran El-Yaniv
JMLR
2010
143views more  JMLR 2010»
13 years 1 days ago
Rademacher Complexities and Bounding the Excess Risk in Active Learning
Sequential algorithms of active learning based on the estimation of the level sets of the empirical risk are discussed in the paper. Localized Rademacher complexities are used in ...
Vladimir Koltchinskii
MA
2010
Springer
132views Communications» more  MA 2010»
13 years 3 months ago
Model selection by sequentially normalized least squares
Model selection by the predictive least squares (PLS) principle has been thoroughly studied in the context of regression model selection and autoregressive (AR) model order estima...
Jorma Rissanen, Teemu Roos, Petri Myllymäki