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Greedy dual iteration search.
We call the resulting algorithm, outlined as follows, Dual iteration search greedy (DIS Greedy).
We call the resulting algorithm, outlined as follows, dual iteration search with prediction (DIS Prediction).
The complexity of subgradient updates is polynomial in the dimension of the dual problem, and thus the complexity of the DIS algorithm is polynomial in the number of users K. Dual iteration search with prediction.
The total utility of all users per time window under DIS Prediction and under DIS Greedy is illustrated in Figure3, as a function of the total downlink power P. We also compare these algorithms to the utility that could be achieved in a non-causal scenario; the curve labeled DIS NC is generated by using a similar dual iteration search algorithm applied to the non-causal problem.
In step 3, the amino acid side chains which contain atoms within a 12 Å distance from the receptor analog are repacked using a heuristic iteration search algorithm to optimize side chain conformations sequentially [46] based on an empirical scoring function parameterized over known HA structures (see Methods S1).
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The OMP is a greedy algorithm that in each iteration searches for the dictionary element that has the biggest inner product with the residual.
The second run, done without iteration, searches against the object database (db2) with the pre-calculated PSSM.
Each search resulted in a list of similar sequences, which was added to the next round of PSI-BLAST iteration searches, and each search continued until no new sequence with an alignment score above the default threshold was retrieved.
In an iterative manner, successive iterations search for new reactions that have all required substrates marked as accessible until no new reaction can be added.
The algorithm starts with the initial atom identifier of the center atom and grows a circular substructure around this atom throughout a defined number of iterations (search depth).
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