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: "distributed channel assignment in cognitive radio networks stable matching and walrasian equilibrium"
  Abstract: We consider a set of secondary transmitter-receiver pairs in a cognitive radio setting. Based on channel sensing and access performances, we consider the problem of assigning channels orthogonally to secondary users through distributed coordination and cooperation algorithms. Two economic models are applied for this purpose: matching markets and competitive markets. In the matching market model, secondary users and channels build two agent sets. We implement a stable matching algorithm in which each secondary user, based on his achievable rate, proposes to the coordinator to be matched with desirable channels. The coordinator accepts or rejects the proposals based on the channel preferences which depend on interference from the secondary user. The coordination algorithm is of low complexity and can adapt to network dynamics. In the competitive market model, channels are associated with prices and secondary users are endowed with monetary budget. Each secondary user, based on his utility function and current channel prices, demands a set of channels. A Walrasian equilibrium maximizes the sum utility and equates the channel demand to their supply. We prove the existence of Walrasian equilibrium and propose a cooperative mechanism to reach it. The performance and complexity of the proposed solutions are illustrated by numerical simulations.

Connected through hyperedge HE-1 (induced by source paper "distributed learning for channel allocation over a shared spectrum"):
  with members:
    - "deep reinforcement learning for dynamic multichannel access in wireless networks"
    - "game of thrones fully distributed learning for multi player bandits"
    - "proactive resource management for lte in unlicensed spectrum a deep learning perspective"
    - "deep multi user reinforcement learning for distributed dynamic spectrum access"
    - "game theoretic dynamic channel allocation for frequency selective interference channels"
    - "proactive resource management in lte u systems a deep learning perspective"
    - "propagation path loss models for 5g urban micro and macro cellular scenarios"
    - "multi player bandits a musical chairs approach"

Connected through hyperedge HE-2 (induced by source paper "distributed task management in cyber physical systems how to cooperate under uncertainty"):
  with members:
    - "distributed user association in energy harvesting small cell networks an exchange economy with uncertainty"
    - "distributed user association in energy harvesting small cell networks a probabilistic bandit model"
    - "minority games with applications to distributed decision making and control in wireless networks"
    - "secondary spectrum auctions for markets with communication constraints"
    - "stackelberg contention games in multiuser networks"

Connected through hyperedge HE-3 (induced by source paper "data and spectrum trading policies in a trusted cognitive dynamic network"):
  with members:
    - "joint resource bidding and tipping strategies in multi hop cognitive networks"
    - "compressed control of complex wireless networks"
    - "flexauc serving dynamic demands in a spectrum trading market with flexible auction"

Connected through hyperedge HE-4 (induced by source paper "deep multi user reinforcement learning for distributed dynamic spectrum access"):
  with members:
    - "deep reinforcement learning for dynamic multichannel access in wireless networks"
    - "approximate best response dynamics in random interference games"
    - "deep learning in mobile and wireless networking a survey"
    - "deep reinforcement one shot learning for artificially intelligent classification systems"
    - "deep reinforcement learning an overview"
    - "active anomaly detection in heterogeneous processes"
    - "proactive resource management in lte u systems a deep learning perspective"
    - "learning to communicate with deep multi agent reinforcement learning"

Connected through hyperedge HE-5 (induced by source paper "applications of economic and pricing models for resource management in 5g wireless networks a survey"):
  with members:
    - "an auction approach to spectrum management in hetnets"
    - "user association in massive mimo hetnets"
    - "applications of economic and pricing models for wireless network security a survey"
    - "caching incentive design in wireless d2d networks a stackelberg game approach"
    - "breaking the economic barrier of caching in cellular networks incentives and contracts"
    - "distributed optimization of hierarchical small cell networks a gnep framework"
    - "spectrum and infrastructure sharing in millimeter wave cellular networks an economic perspective"
    - "caching as a service small cell caching mechanism design for service providers"

Connected through hyperedge HE-6 (induced by source paper "distributed user association in energy harvesting small cell networks an exchange economy with uncertainty"):
  with members:
    - "distributed user association in energy harvesting small cell networks a probabilistic bandit model"
    - "distributed user association in energy harvesting dense small cell networks a mean field multi armed bandit approach"
    - "user association in 5g networks a survey and an outlook"
    - "cooperative interference mitigation and handover management for heterogeneous cloud small cell networks"
    - "optimizing user association and spectrum allocation in hetnets a utility perspective"
    - "a context aware matching game for user association in wireless small cell networks"
    - "matching theory for priority based cell association in the downlink of wireless small cell networks"
    - "a traffic load balancing framework for software defined radio access networks powered by hybrid energy sources"

Connected through hyperedge HE-7 (induced by source paper "blma a blind matching algorithm with application to cognitive radio networks"):
  with members:
    - "matching theory for future wireless networks fundamentals and applications"
    - "distributed resource allocation for relay aided device to device communication a message passing approach"

Connected through hyperedge HE-8 (induced by source paper "a novel collaborative cognitive dynamic network architecture"):
  with members:
    - "a matching game for data trading in operator supervised user provided networks"
    - "matching theory for future wireless networks fundamentals and applications"

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.IT(Information Theory)