Introduces a sampled-input extension to online models bridging worst-case and stochastic settings, with optimal competitive ratios for the secretary problem in worst-case and near-optimal in random-order for small samples, plus an impossibility for simultaneous optimality at large sample sizes.
Secretary p roblems via linear programming
2 Pith papers cite this work. Polarity classification is still indexing.
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cs.DS 2years
2019 2verdicts
UNVERDICTED 2representative citing papers
Presents O(d)-competitive algorithms for d-dimensional online GAP in random-order model with matching lower bound, improving prior 1D results.
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Competitive Analysis with a Sample and the Secretary Problem
Introduces a sampled-input extension to online models bridging worst-case and stochastic settings, with optimal competitive ratios for the secretary problem in worst-case and near-optimal in random-order for small samples, plus an impossibility for simultaneous optimality at large sample sizes.
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Online Multidimensional Packing Problems in the Random-Order Model
Presents O(d)-competitive algorithms for d-dimensional online GAP in random-order model with matching lower bound, improving prior 1D results.