human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "the empirical implications of privacy aware choice"
  Abstract: This paper initiates the study of the testable implications of choice data in settings where agents have privacy preferences. We adapt the standard conceptualization of consumer choice theory to a situation where the consumer is aware of, and has preferences over, the information revealed by her choices. The main message of the paper is that little can be inferred about consumers' preferences once we introduce the possibility that the consumer has concerns about privacy. This holds even when consumers' privacy preferences are assumed to be monotonic and separable. This motivates the consideration of stronger assumptions and, to that end, we introduce an additive model for privacy preferences that does have testable implications.

Connected through hyperedge HE-1 (induced by source paper "dynamically protecting privacy under uncertainty"):
  with members:
    - "query complexity of bayesian private learning"
    - "private sequential learning"
    - "quantifying surveillance in the networked age node based intrusions and group privacy"
    - "perception games and privacy"
    - "riposte an anonymous messaging system handling millions of users"
    - "spy vs spy rumor source obfuscation"
    - "privacy preserving public information for sequential games"
    - "robust adaptive routing under uncertainty"

Connected through hyperedge HE-2 (induced by source paper "query complexity of bayesian private learning"):
  with members:
    - "private sequential learning"
    - "spy vs spy rumor source obfuscation"
    - "differentially private online learning"
    - "iterative constructions and private data release"
    - "differentially private empirical risk minimization"

Connected through hyperedge HE-3 (induced by source paper "plausible deniability in web search from detection to assessment"):
  with members:
    - "plausible deniability for privacy preserving data synthesis"
    - "don t let google know i m lonely"
    - "xray enhancing the web s transparency with differential correlation"
    - "discrimination in online ad delivery"

Connected through hyperedge HE-4 (induced by source paper "perception games and privacy"):
  with members:
    - "truthful mechanisms for agents that value privacy"
    - "privacy aware mechanism design"

Connected through hyperedge HE-5 (induced by source paper "online learning and profit maximization from revealed preferences"):
  with members:
    - "learning economic parameters from revealed preferences"
    - "efficiently learning from revealed preference"

Question: Please tell me which class the center node 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.GT(Computer Science and Game Theory)