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 "strategic classification is causal modeling in disguise"):
  Abstract: Consequential decision-making incentivizes individuals to strategically adapt their behavior to the specifics of the decision rule. While a long line of work has viewed strategic adaptation as gaming and attempted to mitigate its effects, recent work has instead sought to design classifiers that incentivize individuals to improve a desired quality. Key to both accounts is a cost function that dictates which adaptations are rational to undertake. In this work, we develop a causal framework for strategic adaptation. Our causal perspective clearly distinguishes between gaming and improvement and reveals an important obstacle to incentive design. We prove any procedure for designing classifiers that incentivize improvement must inevitably solve a non-trivial causal inference problem. Moreover, we show a similar result holds for designing cost functions that satisfy the requirements of previous work. With the benefit of hindsight, our results show much of the prior work on strategic classification is causal modeling in disguise.

Includes members:
  Member "optimal decision making under strategic behavior":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "decisions counterfactual explanations and strategic behavior")
  Member "understanding agent incentives using causal influence diagrams part i single action settings":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "resolving spurious correlations in causal models of environments via interventions")
  Member "the disparate effects of strategic manipulation":
    also connected through other hyperedges:
      - Hyperedge HE-3 (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-4 (induced by source paper "decisions counterfactual explanations and strategic behavior")
  Member "the social cost of strategic classification":
    also connected through other hyperedges:
      - Hyperedge HE-5 (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-6 (induced by source paper "decisions counterfactual explanations and strategic behavior")
  Member "on the number of experiments sufficient and in the worst case necessary to identify all causal relations among n variables":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "interventional experiment design for causal structure learning")

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)