Math @ Duke
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Papers Published
- Arlotto, A; Xie, X, Logarithmic regret in the dynamic and stochastic knapsack problem with equal rewards,
Stochastic Systems, vol. 10 no. 2
(June, 2020),
pp. 170-191 [doi] [abs]
- Arlotto, A; Frazelle, AE; Wei, Y, Strategic open routing in service networks,
Management Science
(2018), INFORMS
- Arlotto, A; Gurvich, I, Uniformly bounded regret in the multi-secretary problem
(October, 2017) [abs]
- Arlotto, A; Steele, JM, A central limit theorem for temporally nonhomogenous Markov chains with applications to dynamic programming,
Mathematics of Operations Research, vol. 41 no. 4
(November, 2016),
pp. 1448-1468, Institute for Operations Research and the Management Sciences (INFORMS) [doi] [abs]
- Arlotto, A; Mossel, E; Steele, JM, Quickest online selection of an increasing subsequence of specified size,
Random Structures & Algorithms, vol. 49 no. 2
(September, 2016),
pp. 235-252, WILEY [doi] [abs]
- Arlotto, A; Steele, JM, Beardwood–Halton–Hammersley theorem for stationary ergodic sequences: a counterexample,
The Annals of Applied Probability, vol. 26 no. 4
(August, 2016),
pp. 2141-2168, Institute of Mathematical Statistics [doi]
- Arlotto, A; Nguyen, VV; Steele, JM, Optimal online selection of a monotone subsequence: A central limit theorem,
Stochastic Processes and Their Applications, vol. 125 no. 9
(July, 2015),
pp. 3596-3622, Elsevier BV [doi] [abs]
- Arlotto, A; Gans, N; Steele, JM, Markov decision problems where means bound variances,
Operations Research, vol. 62 no. 4
(August, 2014),
pp. 864-875, Institute for Operations Research and the Management Sciences (INFORMS) [doi]
- Arlotto, A; Steele, JM, Optimal Online Selection of an Alternating Subsequence: A Central Limit Theorem,
Advances in Applied Probability, vol. 46 no. 2
(June, 2014),
pp. 536-559, Cambridge University Press (CUP) [doi] [abs]
- Arlotto, A; Chick, SE; Gans, N, Optimal hiring and retention policies for heterogeneous workers who learn,
Management Science, vol. 60 no. 1
(January, 2014),
pp. 110-129, Institute for Operations Research and the Management Sciences (INFORMS) [doi]
- Arlotto, A; Chen, RW; Shepp, LA; Steele, JM, Online Selection of Alternating Subsequences from a Random Sample,
Journal of Applied Probability, vol. 48 no. 4
(December, 2011),
pp. 1114-1132, Cambridge University Press (CUP) [doi] [abs]
- Arlotto, A; Steele, JM, Optimal sequential selection of a unimodal subsequence of a random sequence,
Combinatorics, Probability and Computing, vol. 20 no. 06
(November, 2011),
pp. 799-814, Cambridge University Press (CUP) [doi] [abs]
- Arlotto, A; Gans, N; Chick, S, Optimal employee retention when inferring unknown learning curves, edited by Johansson, B; Jain, S; Montoya-Torres, J; Hugan, J; Yücesan, E,
Proceedings Winter Simulation Conference
(2010),
pp. 1178-1188, IEEE [doi] [abs]
- Arlotto, A; Scarsini, M, Hessian orders and multinormal distributions,
Journal of Multivariate Analysis, vol. 100 no. 10
(November, 2009),
pp. 2324-2330, Elsevier BV [doi] [abs]
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dept@math.duke.edu
ph: 919.660.2800
fax: 919.660.2821
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Mathematics Department
Duke University, Box 90320
Durham, NC 27708-0320
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