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pro vyhledávání: '"Enshaeifar, Shirin"'
Autor:
Li, Honglin, Kolanko, Magdalena Anita, Enshaeifar, Shirin, Skillman, Severin, Markides, Andreas, Kenny, Mark, Soreq, Eyal, Kouchaki, Samaneh, Jensen, Kirsten, Cameron, Loren, Crone, Michael, Freemont, Paul, Rostill, Helen, Sharp, David J., Nilforooshan, Ramin, Barnaghi, Payam
Machine learning techniques combined with in-home monitoring technologies provide a unique opportunity to automate diagnosis and early detection of adverse health conditions in long-term conditions such as dementia. However, accessing sufficient labe
Externí odkaz:
http://arxiv.org/abs/2011.13916
Conventional deep learning models have limited capacity in learning multiple tasks sequentially. The issue of forgetting the previously learned tasks in continual learning is known as catastrophic forgetting or interference. When the input data or th
Externí odkaz:
http://arxiv.org/abs/2005.05080
Akademický článek
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Continual learning models allow to learn and adapt to new changes and tasks over time. However, in continual and sequential learning scenarios in which the models are trained using different data with various distributions, neural networks tend to fo
Externí odkaz:
http://arxiv.org/abs/1910.04112
Learning and adapting to new distributions or learning new tasks sequentially without forgetting the previously learned knowledge is a challenging phenomenon in continual learning models. Most of the conventional deep learning models are not capable
Externí odkaz:
http://arxiv.org/abs/1905.08119
Learning in a non-stationary environment is an inevitable problem when applying machine learning algorithm to real world environment. Learning new tasks without forgetting the previous knowledge is a challenge issue in machine learning. We propose a
Externí odkaz:
http://arxiv.org/abs/1811.02361
Autor:
Enshaeifar, Shirin
One of the earlier works on eigen-based techniques for the hyper-complex domain of quaternions was on “quaternion principal component analysis of colour images”. The results of this work are still instructive in many aspects. First, it showed how
Externí odkaz:
http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.690419
This work addresses the problem of segmentation in time series data with respect to a statistical parameter of interest in Bayesian models. It is common to assume that the parameters are distinct within each segment. As such, many Bayesian change poi
Externí odkaz:
http://arxiv.org/abs/1710.09657
Autor:
Xiang, Min, Enshaeifar, Shirin, Stott, Alexander E., Took, Clive Cheong, Xia, Yili, Kanna, Sithan, Mandic, Danilo P.
Recent developments in quaternion-valued widely linear processing have established that the exploitation of complete second-order statistics requires consideration of both the standard covariance and the three complementary covariance matrices. Altho
Externí odkaz:
http://arxiv.org/abs/1705.00058
Autor:
Xiang, Min, Enshaeifar, Shirin, Stott, Alexander E., Took, Clive Cheong, Xia, Yili, Kanna, Sithan, Mandic, Danilo P.
Publikováno v:
In Signal Processing July 2018 148:193-204