Regularized Online Allocation Problems: Fairness and Beyond
Published Online:20 Feb 2025https://doi.org/10.1287/msom.2022.0212
References
- (2015) Fast algorithms for online stochastic convex programming. Proc. Twenty-Sixth Annual ACM-SIAM Sympos. Discrete Algorithms, SODA β15 (Society for Industrial and Applied Mathematics, Philadelphia), 1405β1424.Google Scholar
- (2016) An efficient algorithm for contextual bandits with knapsacks, and an extension to concave objectives. Feldman V, Rakhlin A, Shamir O, eds. 29th Annual Conf. Learning Theory (PMLR, New York), 4β18.Google Scholar
- (2014) A dynamic near-optimal algorithm for online linear programming. Oper. Res. 62(4):876β890.Link,Β Google Scholar
- (2018) Proportional allocation: Simple, distributed, and diverse matching with high entropy. Dy J, Krause A, eds. Proc. 35th Internat. Conf. Machine Learn. (PMLR, New York), 99β108.Google Scholar
- (2017) Diverse weighted bipartite b-matching. Proc. 26th Internat. Joint Conf. Artificial Intelligence (AAAI Press, Palo Alto, CA), 35β41.Google Scholar
- (2019) Uniformly bounded regret in the multisecretary problem. Stoch. Syst. 9(3):231β260.Link,Β Google Scholar
- (2010) How to allocate goods in an online market? de Berg M, Meyer U, eds. Eur. Sympos. Algorithms (Springer Berlin Heidelberg, Berlin, Heidelberg), 51β62.Google Scholar
- (2018) Bandits with knapsacks. J. ACM 65(3):1β55.Crossref,Β Google Scholar
- (2009) Toward robust revenue management: Competitive analysis of online booking. Oper. Res. 57(4):950β963.Link,Β Google Scholar
- (2019) Learning in repeated auctions with budgets: Regret minimization and equilibrium. Management Sci. 65(9):3952β3968.Link,Β Google Scholar
- (2020) The best of many worlds: Dual mirror descent for online allocation problems. Preprint, submitted November 18, https://doi.org/10.48550/arXiv.2011.10124.Google Scholar
- Balseiro SR, Lu H, Mirrokni V (2021) Regularized online allocation problems: Fairness and beyond. Meila M, Zhang T, eds. Proc. 38th Internat. Conf. Machine Learn. (PMLR, New York), 630β639.Google Scholar
- (2023) The best of many worlds: Dual mirror descent for online allocation problems. Oper. Res. 71(1):101β119.Link,Β Google Scholar
- (2014) Yield optimization of display advertising with ad exchange. Management Sci. 60(12):2886β2907.Link,Β Google Scholar
- (2006) The Santa Claus problem. Proc. Thirty-Eighth Annual ACM Sympos. Theory Comput. (Association for Computing Machinery, New York), 31β40.Google Scholar
- (2018) Fair resource allocation in a volatile marketplace. Preprint, submitted October 21, http://dx.doi.org/10.2139/ssrn.2789380.Google Scholar
- (2009) Convex Optimization Theory (Athena Scientific, Belmont, MA).Google Scholar
- (2011) The price of fairness. Oper. Res. 59(1):17β31.Link,Β Google Scholar
- (2012) On the efficiency-fairness trade-off. Management Sci. 58(12):2234β2250.Link,Β Google Scholar
- (2004) Convex Optimization (Cambridge University Press, Cambridge, UK).Crossref,Β Google Scholar
- (2015) Convex optimization: Algorithms and complexity. Foundations Trends Machine Learn. 8(3β4):231β357.Crossref,Β Google Scholar
- (2007) Online primal-dual algorithms for maximizing ad-auctions revenue. Arge L, Hoffmann M, Welzl E, eds. Algorithms β ESA 2007 (Springer Berlin Heidelberg, Berlin, Heidelberg), 253β264.Crossref,Β Google Scholar
- (2015) When algorithms discriminate. New York Times (July 9), https://www.nytimes.com/2015/07/10/upshot/when-algorithms-discriminate.html.Google Scholar
- (2021) The parity ray regularizer for pacing in auction markets. Preprint, submitted June 17, https://doi.org/10.48550/arXiv.2106.09503.Google Scholar
- (2020) Online planning with offline simulation. Available at SSRN 3709882.Google Scholar
- (2009) The adwords problem: Online keyword matching with budgeted bidders under random permutations. Proc. 10th ACM Conf. Electronic Commerce, EC β09 (Association for Computing Machinery, New York), 71β78.Google Scholar
- (2012) Online matching with concave returns. Proc. Forty-Fourth Annual ACM Sympos. Theory Comput., STOC β12 (Association for Computing Machinery, New York), 137β144.Google Scholar
- (2019) Near optimal online algorithms and fast approximation algorithms for resource allocation problems. J. ACM 66(1):1β41.Crossref,Β Google Scholar
- (2019) Balancing relevance and diversity in online bipartite matching via submodularity. AAAI 33(November):1877β1884.Crossref,Β Google Scholar
- (2016) Designing smoothing functions for improved worst-case competitive ratio in online optimization. Lee D, Sugiyama M, Luxburg U, Guyon I, Garnett R, eds. Adv. Neural Inform. Processing Systems (Curran Associates, Inc., Red Hook, NY), 3287β3295.Google Scholar
- (2020) Fair allocation of scarce medical resources in the time of covid-19. N Engl. J. Med. 382(21):2049β2055.Crossref,Β Google Scholar
- (2010) Online stochastic packing applied to display ad allocation. DeBerg M, Meyer U, eds. Proc. 18th Annual Eur. Conf. Algorithms Part I ESA β10 (Springer-Verlag, Berlin, Heidelberg), 182β194.Google Scholar
- (2009) Online ad assignment with free disposal. Leonardi S, ed. Proc. 5th Internat. Workshop Internet Network Economics WINE β09 (Springer-Verlag, Berlin, Heidelberg), 374β385.Google Scholar
- (2016) Introduction to online convex optimization. Foundations Trends Optim. 2(3β4):157β325.Crossref,Β Google Scholar
- (2015) Performance of an lp-based control for revenue management with unknown demand parameters. Oper. Res. 63(4):909β915.Link,Β Google Scholar
- (2016) Online optimization and regret guarantees for non-additive long-term constraints. Preprint, submitted February 17, https://arxiv.org/abs/1602.05394.Google Scholar
- (2025) Online stochastic optimization with Wasserstein based non-stationarity. Management Sci. Forthcoming.Link,Β Google Scholar
- (2019) Achieving high individual service-levels without safety stock? Optimal rationing policy of pooled resources. Preprint, submitted August 22, http://dx.doi.org/10.2139/ssrn.3385089.Google Scholar
- (1990) An optimal algorithm for on-line bipartite matching. Bodlaender HL, Italiano GF, eds. Proc. Twenty-Second Annual ACM Sympos. Theory Comput. (Springer Berlin Heidelberg, Berlin, Heidelberg), 352β358.Google Scholar
- (2021) Online linear programming: Dual convergence, new algorithms, and regret bounds. Preprint, submitted September 12, https://arxiv.org/abs/1909.05499.Google Scholar
- (2020) Simple and fast algorithm for binary integer and online linear programming. Preprint, submitted March 5, https://doi.org/10.48550/arXiv.2003.02513.Google Scholar
- (2014) Sequential resource allocation for nonprofit operations. Oper. Res. 62(2):301β317.Link,Β Google Scholar
- Lobos A, Grigas P, Wen Z, Lee K (2018) Optimal bidding, allocation and budget spending for a demand side platform under many auction types. Preprint, submitted May 29, https://arxiv.org/abs/1805.11645.Google Scholar
- (2018) Stochastic bandits robust to adversarial corruptions. Diakonikolas I, Kempe D, Henzinger M, eds. Proc. 50th Annual ACM SIGACT Sympos. Theory Comput. (ACM, New York), 114β122.Google Scholar
- (2020) Algorithms for online matching, assortment, and pricing with tight weight-dependent competitive ratios. Oper. Res. 68(6):1787β1803.Link,Β Google Scholar
- (2020) Group-level fairness maximization in online bipartite matching. Preprint, submitted November 27, https://arxiv.org/abs/2011.13908.Google Scholar
- (2021) Fair dynamic rationing. EC β21 (Association for Computing Machinery, New York), 694β695.Google Scholar
- (2013) Online matching and ad allocation. Foundations Trends Theoret. Comput. Sci. 8(4):265β368.Crossref,Β Google Scholar
- (2007) Adwords and generalized online matching. J. ACM 54(5):22βes.Crossref,Β Google Scholar
- (2012) Simultaneous Approximations for Adversarial and Stochastic Online Budgeted Allocation (Association for Computing Machinery, New York), 1690β1701.Google Scholar
- (2000) Fair end-to-end window-based congestion control. IEEE/ACM Trans. Networking 8(5):556β567.Crossref,Β Google Scholar
- (2020) Balancing the tradeoff between profit and fairness in rideshare platforms during high-demand hours. Proc. AAAI Conf. Artificial Intelligence, vol. 34 (Association for Computing Machinery, New York), 2210β2217.Google Scholar
- (1950) The bargaining problem. Econometrica 18(2):155β162.Crossref,Β Google Scholar
- (2020) Mechanism design for online resource allocation: A unified approach. Abstr. 2020 SIGMETRICS/Performance Joint Internat. Conf. Measurement Modeling Comput. Systems (Association for Computing Machinery, New York), 11β12.Google Scholar
- (2013) Dynamic cloud pricing for revenue maximization. IEEE Trans. Cloud Comput. 1(2):158β171.Crossref,Β Google Scholar

