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: "wireless capacity with arbitrary gain matrix"
  Abstract: Given a set of wireless links, a fundamental problem is to find the largest subset that can transmit simultaneously, within the SINR model of interference. Significant progress on this problem has been made in recent years. In this note, we study the problem in the setting where we are given a fixed set of arbitrary powers each sender must use, and an arbitrary gain matrix defining how signals fade. This variation of the problem appears immune to most algorithmic approaches studied in the literature. Indeed it is very hard to approximate since it generalizes the max independent set problem. Here, we propose a simple semi-definite programming approach to the problem that yields constant factor approximation, if the optimal solution is strictly larger than half of the input size.

Connected through hyperedge HE-1 (induced by source paper "reception capacity definitions game theory and hardness"):
  with members:
    - "how well can graphs represent wireless interference"
    - "algorithms for wireless capacity"
    - "wireless connectivity and capacity"
    - "wireless capacity with oblivious power in general metrics"
    - "a constant factor approximation for wireless capacity maximization with power control in the sinr model"
    - "on a game theoretic approach to capacity maximization in wireless networks"

Connected through hyperedge HE-2 (induced by source paper "reception capacity through perfect domination"):
  with members:
    - "how well can graphs represent wireless interference"
    - "braess s paradox in wireless networks the danger of improved technology"
    - "algorithms for wireless capacity"
    - "wireless connectivity and capacity"
    - "wireless capacity with oblivious power in general metrics"
    - "a constant factor approximation for wireless capacity maximization with power control in the sinr model"
    - "on a game theoretic approach to capacity maximization in wireless networks"

Connected through hyperedge HE-3 (induced by source paper "maximal packing with interference constraints"):
  with members:
    - "how well can graphs represent wireless interference"
    - "algorithms for wireless capacity"
    - "a constant factor approximation for wireless capacity maximization with power control in the sinr model"
    - "wireless scheduling with power control"

Connected through hyperedge HE-4 (induced by source paper "beyond geometry towards fully realistic wireless models"):
  with members:
    - "wireless scheduling algorithms in complex environments"
    - "jamming resistant learning in wireless networks"
    - "distributed deterministic broadcasting in uniform power ad hoc wireless networks"
    - "online independent set beyond the worst case secretaries prophets and periods"
    - "approximation algorithms for wireless link scheduling with flexible data rates"
    - "distributed connectivity of wireless networks"
    - "mlls minimum length link scheduling under physical interference model"
    - "the power of non uniform wireless power"

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.DS(Data Structures and Algorithms)