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Published in 2017 at "IEEE Transactions on Information Theory"
DOI: 10.1109/tit.2017.2735799
Abstract: We study online learning under logarithmic loss with regular parametric models. In this setting, each strategy corresponds to a joint distribution on sequences. The minimax optimal strategy is the normalized maximum likelihood (NML) strategy. We…
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Keywords:
normalized maximum;
maximum likelihood;
characterizes optimality;
strategy ... See more keywords
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Published in 2021 at "IEEE Transactions on Information Theory"
DOI: 10.1109/tit.2021.3088304
Abstract: Normalized maximum likelihood (NML) distribution of probabilistic model gives the optimal code length function in the sense of minimax regret. Despite its optimal property, the calculation of NML distribution is not easy, and existing efficient…
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Keywords:
maximum likelihood;
fourier analysis;
distribution;
nml distribution ... See more keywords
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Published in 2024 at "IEEE Transactions on Information Theory"
DOI: 10.1109/tit.2024.3406926
Abstract: Machine learning systems require massive amounts of labeled training data in order to achieve high accuracy rates. Active learning uses feedback to label the most informative data points and significantly reduce the training set size.…
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Keywords:
criterion;
predictive normalized;
normalized maximum;
active learning ... See more keywords
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Published in 2018 at "EURASIP Journal on Advances in Signal Processing"
DOI: 10.1186/s13634-018-0581-5
Abstract: An adaptive combination constrained proportionate normalized maximum correntropy criterion (ACC-PNMCC) algorithm is proposed for sparse multi-path channel estimation under mixed Gaussian noise environment. The developed ACC-PNMCC algorithm is implemented by incorporating an adaptive combination function…
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Keywords:
normalized maximum;
adaptive combination;
maximum correntropy;
pnmcc algorithm ... See more keywords