Results 111 to 120 of about 25,302 (170)
Optimizing Tourism Routes: A Quantum Approach to the Profitable Tour Problem. [PDF]
Entropy (Basel)Cheng XS, Liu YH, Dong XH, Wang Y.
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EvoThy-Net: an evolutionary encoder-decoder network for thyroid nodule segmentation in ultrasound imaging. [PDF]
Sci RepGanne NS, Balakrishna S.
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The Ground-Set-Cost Budgeted Maximum Coverage Problem. [PDF]
Theory Comput Systvan Heuven van Staereling I +2 more
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Toward intelligent IoT scheduling with quantum-inspired latent models for energy and latency optimization. [PDF]
Sci RepAlyas T +6 more
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A compressive sensing-driven data collection scheme for UAV-assisted wireless sensor networks. [PDF]
Sci RepHan Z, Zheng G, Li C, Wang G, Mu Y.
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Mathematical Notes, 2022
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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1995
We consider the selection of two basketball teams at a neighborhood playground to illustrate the greedy method. Usually the top two players are designated captains. All other players line up while the captains alternate choosing one player at a time. Usually, the players are picked using a greedy strategy.
Raymond Greenlaw +2 more
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We consider the selection of two basketball teams at a neighborhood playground to illustrate the greedy method. Usually the top two players are designated captains. All other players line up while the captains alternate choosing one player at a time. Usually, the players are picked using a greedy strategy.
Raymond Greenlaw +2 more
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Mathematical Notes, 2021
We introduce and study a new type of greedy algorithm, namely, projection greedy algorithms with respect to a given dictionary in a Hilbert space. We prove that these algorithms converge and estimate the rate of convergence for initial elements from the convex hull of the dictionary.
P. A. Borodin, S. V. Konyagin
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We introduce and study a new type of greedy algorithm, namely, projection greedy algorithms with respect to a given dictionary in a Hilbert space. We prove that these algorithms converge and estimate the rate of convergence for initial elements from the convex hull of the dictionary.
P. A. Borodin, S. V. Konyagin
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