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 "causal feature discovery through strategic modification"):
  Abstract: We consider an online regression setting in which individuals adapt to the regression model: arriving individuals may access the model throughout the process, and invest strategically in modifying their own features so as to improve their assigned score. We find that this strategic manipulation may help a learner recover the causal variables, in settings where an agent can invest in improving impactful features that also improve his true label. We show that even simple behavior on the learner's part (i.e., periodically updating her model based on the observed data so far, via least-square regression) allows her to simultaneously i) accurately recover which features have an impact on an agent's true label, provided they have been invested in significantly, and ii) incentivize agents to invest in these impactful features, rather than in features that have no effect on their true label.

Includes members:
  Member "strategic adaptation to classifiers a causal perspective":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "decisions counterfactual explanations and strategic behavior")
  Member "the disparate effects of strategic manipulation":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "decisions counterfactual explanations and strategic behavior")
  Member "how do classifiers induce agents to invest effort strategically":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "decisions counterfactual explanations and strategic behavior")
  Member "the social cost of strategic classification":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "no computation without representation avoiding data and algorithm biases through diversity")
  Member "strategic classification from revealed preferences":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "decisions counterfactual explanations and strategic behavior")
  Member "truthful linear regression":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "mechanism design for multi party machine learning")
  Member "budget feasible mechanisms for experimental design":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "towards data auctions with externalities")
  Member "buying private data without verification":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "prospect theoretic analysis of privacy preserving mechanism")

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.LG(Machine Learning)