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His research interests broadly include quantum computation, quantum chemistry, numerical methods, and information sparsity.
To counter the problem of channel sparsity information, sparsity adaptive matching pursuit (SAMP) was proposed in [25].
In the previous section, we presented the details of the OC method that combines a priori statistical information, sparsity, and structure of the sensing matrix to develop a fast and low-complexity sparse RIR reconstruction algorithm.
In the control group, corresponding place field characteristics, including spatial information sparsity and place field size, remained stable across 6 recording sessions.
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However, when the system does not have sufficient historical information (referred to as the data sparsity issue presented in Moreno [76]), then the recommendations are not reliable.
This is caused by the data sparsity issue in recommender systems, where little existing rating information is available.
Firstly, most of the existing recommendation approaches are based on single information source and cannot effectively solve the cold start and data sparsity problems.
Most of the existing recommendation approaches are based on single information source and cannot effectively solve the cold start and data sparsity problems.
One of the weaknesses of this work is that no second-hand information is considered for trust computation that may result in bootstrapping and data sparsity problem [14].
Figure 9 shows that by alternate projections between information and sparsity domains (adaptively lowering or raising the threshold levels in the sparsity domain), the sparse coefficients are gradually picked up after several iterations.
For a perfectly known state model, extra information like sparsity and non-negativity does not play any significant role in terms of estimation accuracy.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com