human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "a differentially private incentive design for traffic offload to public transportation"):
  Abstract: Increasingly large trip demands have strained urban transportation capacity, which consequently leads to traffic congestion. In this work, we focus on mitigating traffic congestion by incentivizing passengers to switch from private to public transit services. We address the following challenges. First, the passengers incur inconvenience costs when participating in traffic offload due to delay and discomfort, and thus need to be reimbursed. The inconvenience cost, however, is unknown to the government when choosing the incentives. Furthermore, participating in traffic offload raises privacy concerns from passengers. An adversary could infer personal information, (e.g., daily routine, region of interest, and wealth), by observing the decisions made by the government, which are known to the public. We adopt the concept of differential privacy and propose privacy-preserving incentive designs under two settings, denoted as two-way communication and one-way communication. Under two-way communication, we focus on how the government should reveal passengers' inconvenience costs to properly incentivize them while preserving differential privacy. We formulate the problem as a mixed integer linear program, and propose a polynomial-time approximation algorithm. We show the proposed approach achieves truthfulness, individual rationality, social optimality, and differential privacy. Under one-way communication, we focus on how the government should design the incentives without revealing passengers' inconvenience costs while still preserving differential privacy. We formulate the problem as a convex program, and propose a differentially private and near-optimal solution algorithm. A numerical case study using Caltrans Performance Measurement System (PeMS) data source is presented as evaluation.

Includes members:
  Member "model predictive control of autonomous mobility on demand systems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on the interaction between autonomous mobility on demand systems and power distribution networks an optimal power flow approach")
  Member "dynamic vehicle redistribution and online price incentives in shared mobility systems":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "role detection in bicycle sharing networks using multilayer stochastic block models")
  Member "the exponential mechanism for social welfare private truthful and nearly optimal":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "segmentation incentives and privacy")

Question: Please tell me which class the source paper belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.CY(Computers and Society)