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作者：He, Shengyi; Jiang, Guangxin; Lam, Henry; Fu, Michael C.
作者单位：Columbia University; Harbin Institute of Technology; University System of Maryland; University of Maryland College Park; University System of Maryland; University of Maryland College Park
摘要：In solving simulation-based stochastic root-finding or optimization problems that involve rare events, such as in extreme quantile estimation, running crude Monte Carlo can be prohibitively inefficient. To address this issue, importance sampling can be employed to drive down the sampling error to a desirable level. However, selecting a good importance sampler requires knowledge of the solution to the problem at hand, which is the goal to begin with and thus forms a circular challenge. We inves...
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作者：Lee, Ilbin
作者单位：University of Alberta
摘要：In recent applications of Markov decision processes (MDPs), it is common to estimate transition probabilities and rewards from transition data. In healthcare and some other applications, transition data are collected from a population of different entities, such as patients. Thus, one faces a modeling question of whether to estimate different models for subpopulations (e.g., divided by smoking status). For instance, there may be a subpopulation whose disease status progresses faster than other...
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作者：Karlin, Anna R.; Klein, Nathan; Gharan, Shayan Oveis
作者单位：University of Washington; University of Washington Seattle
摘要：For some epsilon > 10(-36), we give a randomized 3/2 - epsilon approximation algorithm for metric TSP.
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作者：Zhou, Yi; Fu, Michael C.; Ryzhov, Ilya O.
作者单位：University System of Maryland; University of Maryland College Park; University System of Maryland; University of Maryland College Park; University System of Maryland; University of Maryland College Park
摘要：We consider the problem of selecting the best alternative in a setting where prior similarity information between the performance output of different alternatives can be learned from data. Incorporating similarity information enables efficient budget allocation for faster identification of the best alternative in sequential selection. Using a new selection criterion, the similarity selection index, we develop two new allocation methods: one based on a mathematical programming characterization ...
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作者：Kondratev, Aleksei Y.; Ianovski, Egor; Nesterov, Alexander S.
作者单位：HSE University (National Research University Higher School of Economics)
摘要：Scoring rules are widely used to rank athletes in sports and candidates in elections. Each position in each individual ranking is worth a certain number of points; the total sum of points determines the aggregate ranking. The question is how to choose a scoring rule for a specific application. First, we derive a one-parameter family with geometric scores that satisfies two principles of independence: once an extremely strong or weak candidate is removed, the aggregate ranking ought to remain i...
