Filters








43 Hits in 2.2 sec

Mechanism Design for Crowdsourcing: An Optimal 1-1/e Competitive Budget-Feasible Mechanism for Large Markets [article]

Nima Anari, Gagan Goel, Afshin Nikzad
2014 arXiv   pre-print
In this paper, we design a budget-feasible mechanism for large markets that achieves an approximation factor of 1-1/e (i.e. almost 0.63).  ...  In this paper we consider a mechanism design problem in the context of large-scale crowdsourcing markets such as Amazon's Mechanical Turk, ClickWorker, CrowdFlower.  ...  Acknowledgments We acknowledge the comments and ideas of an anonymous reviewer that helped us generalize our impossibility result to the case of bayesian setting.  ... 
arXiv:1405.2452v3 fatcat:w5izej4klrayhlqidtvdlmi2ie

Truthful Mechanism Design for Multiregion Mobile Crowdsensing

Yu Qiao, Jun Wu, Hao Cheng, Zilan Huang, Qiangqiang He, Chongjun Wang
2020 Wireless Communications and Mobile Computing  
We design two objectives for the proposed multiregion scenario, namely, weighted mean and maximin.  ...  However, existing mechanisms failed to consider situations where the crowdsourcer has to hire capacitated workers or workers from multiregions.  ...  Anari et al. investigated a model to solve the mechanism design problem in the context of large-scale crowdsensing markets such as Amazon's Mechanical Turk [26] .  ... 
doi:10.1155/2020/8834983 fatcat:pnjpigozh5eondhqftdyyfj6ny

Budget-Feasible Online Incentive Mechanisms for Crowdsourcing Tasks Truthfully

Dong Zhao, Xiang-Yang Li, Huadong Ma
2016 IEEE/ACM Transactions on Networking  
We design two online mechanisms, OMZ and OMG, satisfying the computational efficiency, individual rationality, budget feasibility, truthfulness, consumer sovereignty and constant competitiveness under  ...  To achieve good service quality for an MCS application, incentive mechanisms are necessary to attract more user participation.  ...  More recently, there are some studies on online mechanism design for crowdsourcing markets [17] - [19] . Singer et al. [17] and Singla et al.  ... 
doi:10.1109/tnet.2014.2379281 fatcat:77ivszh335c7fn4glhwsg3b3ki

OMG: How Much Should I Pay Bob in Truthful Online Mobile Crowdsourced Sensing? [article]

Dong Zhao, Xiang-Yang Li, Huadong Ma
2013 arXiv   pre-print
We design two online mechanisms, OMZ and OMG, satisfying the computational efficiency, individual rationality, budget feasibility, truthfulness, consumer sovereignty and constant competitiveness under  ...  for maximizing the total value of the services provided by selected users under a budget constraint.  ...  It is known that a greedy algorithm provides a (11/e)-approximation solution [23] . The second benchmark is the proportional share mechanism in the offline scenario (Algorithm 3).  ... 
arXiv:1306.5677v1 fatcat:mvcqqwdi45f4bc732qcagxzx34

Power of Bonus in Pricing for Crowdsourcing [article]

Suho Shin, Hoyong Choi, Yung Yi, Jungseul Ok
2021 arXiv   pre-print
Such a pricing form is widely adopted in practice for its simplicity, e.g., Amazon Mechanical Turk, although additional sophistication to pricing rule can enhance budget efficiency.  ...  We consider a simple form of pricing for a crowdsourcing system, where pricing policy is published a priori, and workers then decide their task acceptance.  ...  Mechanism design for crowdsourcing: An optimal 1-1/e competitive budget-feasible mechanism for large markets. In Proc. of FOCS, 2014. [AKK12] Vineet Abhishek, Ian A Kash, and Peter Key.  ... 
arXiv:1804.03178v4 fatcat:6i4u3lgqonh7bbcvvw2knxhaqu

Budget Feasible Procurement Auctions

Nima Anari, Gagan Goel, Afshin Nikzad
2018 Operations Research  
An alternative way to write the assumption is c max = o(B); in other words, we define bid-budget ratio of the market to be θ = cmax B and analyze our mechanisms for when θ → 0.  ...  A mechanism M is α-competitive when α ∈ [0, 1] is the largest scalar for which the mechanism derives utility at least α · U * (c, u) for all c and u.  ...  Any truthful budget feasible mechanism attains competitive ratio at most 11/e.  ... 
doi:10.1287/opre.2017.1693 fatcat:2jze4wzncnbnbndyssbsl3xkfa

A Unified Model for the Two-stage Offline-then-Online Resource Allocation [article]

Yifan Xu, Pan Xu, Jianping Pan, Jun Tao
2020 arXiv   pre-print
Both offline and online resource allocation have wide applications in various real-world matching markets ranging from ridesharing to crowdsourcing.  ...  The process consists of an offline phase and another sequential online phase, and both phases compete for the same set of resources.  ...  The authors would like to thank the anonymous reviewers for their helpful feedback.  ... 
arXiv:2012.06845v1 fatcat:yg6r5ehubjhftgys4przwhqfie

Crowd Access Path Optimization: Diversity Matters [article]

Besmira Nushi, Adish Singla, Anja Gruenheid, Erfan Zamanian, Andreas Krause, Donald Kossmann
2015 arXiv   pre-print
Our results show that the Access Path Model combined with greedy optimization is cost-efficient and practical to overcome common difficulties in large-scale crowdsourcing like data sparsity and anonymity  ...  Moreover, we devise a greedy optimization algorithm for this model that finds a provably good approximate plan to access the crowd.  ...  The authors would also like to thank Brian Galebach and Sharad Goel for providing the Probability Sports dataset.  ... 
arXiv:1508.01951v2 fatcat:grakbwrewnf25iuj7tgwnv2umm

Lifted Hybrid Variational Inference

Yuqiao Chen, Yibo Yang, Sriraam Natarajan, Nicholas Ruozzi
2020 Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence  
Additionally, we present a sufficient condition for the Bethe variational approximation to yield a non-trivial estimate over the marginal polytope.  ...  We demonstrate that the proposed variational methods are highly scalable and can exploit approximate model symmetries even in the presence of a large amount of continuous evidence, outperforming existing  ...  The authors would like to thank the anonymous reviewers for their helpful feedback. Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence  ... 
doi:10.24963/ijcai.2020/581 dblp:conf/ijcai/0002X0T20 fatcat:d46tftuwhvbt3lwiw5fn6dnh4m

Bayesian Mechanism Design

Aranyak Mehta
2013 Foundations and Trends® in Theoretical Computer Science  
This will prove: ALG = Primal ≥ 1 ρ Dual ≥ 1 ρ Dual * ≥ 1 ρ OPT proving a competitive ratio of 1/ρ = 11 e . (1) Feasibility.  ...  As before, to prove that this algorithm achieves 11 e , we need to prove the competitive ratio and feasibility. Primal-Dual ratio.  ... 
doi:10.1561/0400000057 fatcat:a7zzdglqmndh3bwdcxiklxoicu

Balancing the Tradeoff between Profit and Fairness in Rideshare Platforms During High-Demand Hours [article]

Vedant Nanda and Pan Xu and Karthik Abinav Sankararaman and John P. Dickerson and Aravind Srinivasan
2020 arXiv   pre-print
We formalize the measures of profit and fairness in our setting and show that by using , the competitive ratios for profit and fairness measures would be no worse than α/e and β/e respectively.  ...  We model the matching problem as an online bipartite matching where the set of drivers is offline and requests arrive online.  ...  No non-adaptive algorithm can achieve a (α, β)-competitive ratio simultaneously on the profit and fairness with α + β > 11/e using LP-(1) and LP-(2) as the benchmark.  ... 
arXiv:1912.08388v2 fatcat:ytnk2grdbrehhk4yyfxw5aivei

Balancing the Tradeoff between Profit and Fairness in Rideshare Platforms during High-Demand Hours

Vedant Nanda, Pan Xu, Karthik Abinav Sankararaman, John P. Dickerson, Aravind Srinivasan
2020 Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society  
We formalize the measures of profit and fairness in our setting and show that by using NAdap, the competitive ratios for profit and fairness measures would be no worse than α/e and β/e respectively.  ...  We model the matching problem as an online bipartite matching where the set of drivers is offline and requests arrive online.  ...  Acknowledgements We would like to thank anonymous reviewers for their helpful comments. Nanda and Dickerson were supported by NSF CAREER Award IIS-1846237 and DARPA SI3-CMD Award S4761.  ... 
doi:10.1145/3375627.3375818 dblp:conf/aies/Nanda0SDS20 fatcat:ju3umvzn7vbd7gm6i7gtnnjiji

Balancing the Tradeoff between Profit and Fairness in Rideshare Platforms during High-Demand Hours

Vedant Nanda, Pan Xu, Karthik Abhinav Sankararaman, John Dickerson, Aravind Srinivasan
2020 PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE  
We formalize the measures of profit and fairness in our setting and show that by using NAdap, the competitive ratios for profit and fairness measures would be no worse than α/e and β/e respectively.  ...  We model the matching problem as an online bipartite matching where the set of drivers is offline and requests arrive online.  ...  Acknowledgements We would like to thank anonymous reviewers for their helpful comments. Nanda and Dickerson were supported by NSF CAREER Award IIS-1846237 and DARPA SI3-CMD Award S4761.  ... 
doi:10.1609/aaai.v34i02.5597 fatcat:wsd5gwqcpfdpzcnv6hc5fyx6kq

Enhancing knowledge acquisition systems with user generated and crowdsourced resources [article]

Fang Xu, Universität Des Saarlandes, Universität Des Saarlandes
2013
"Crowdsourcing" bedeutet, eine Aufgabe via Internet an eine große Menge an angeworbene Menschen zu verteilen, die diese simultan erledigen.  ...  The second strategy is on creating annotation for QA systems with the help of crowdsourcing.  ...  Then for worker j for passage i, the posterior probability for x i = 1 is defined as, P (l ij = x i |α j , β i ) = 1 1 + e −α j /β i (7.8) The EM algorithm is designed as an efficient iterative algorithm  ... 
doi:10.22028/d291-22919 fatcat:ebrgqxukdvap7i3i2lizmwykgq

New Models and Methods for Formation and Analysis of Social Networks [article]

Swapnil Dhamal
2017 arXiv   pre-print
With the objective of achieving better diffusion, we discover optimal ways of splitting the available budget among the phases, determining the time delay between consecutive phases, and also finding the  ...  In particular, we develop models and methods for solving the above problems, which primarily deal with formation and analysis of social networks.  ...  Since greedy hill-climbing provides a 11 e -approximation to the optimal solution, we have ρ(S G ) = min i∈N c(S G , i) ≥ 11 e ρ * =⇒ 1 − max i∈N d(S G , i) ≥ 11 e ρ * =⇒ max i∈N d(S G , i) ≤  ... 
arXiv:1706.09310v1 fatcat:gd2jxhuqzfdotmiq5anoon4vm4
« Previous Showing results 1 — 15 out of 43 results