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: "decoding delay minimization in inter session network coding"
  Abstract: Intra-session network coding has been shown to offer significant gains in terms of achievable throughput and delay in settings where one source multicasts data to several clients. In this paper, we consider a more general scenario where multiple sources transmit data to sets of clients over a wireline overlay network. We propose a novel framework for efficient rate allocation in networks where intermediate network nodes have the opportunity to combine packets from different sources using randomized network coding. We formulate the problem as the minimization of the average decoding delay in the client population and solve it with a gradient-based stochastic algorithm. Our optimized inter-session network coding solution is evaluated in different network topologies and is compared with basic intra-session network coding solutions. Our results show the benefits of proper coding decisions and effective rate allocation for lowering the decoding delay when the network is used by concurrent multicast sessions.

Connected through hyperedge HE-1 (induced by source paper "network coding based evolutionary network formation for dynamic wireless networks"):
  with members:
    - "distributed rate allocation in inter session network coding"
    - "random linear network coding for wireless layered video broadcast general design methods for adaptive feedback free transmission"
    - "enabling wireless power transfer in cellular networks architecture modeling and deployment"
    - "mac centered cooperation synergistic design of network coding multi packet reception and improved fairness to increase network throughput"
    - "coding for errors and erasures in random network coding"

Connected through hyperedge HE-2 (induced by source paper "distributed topology design for network coding deployed large scale sensor networks"):
  with members:
    - "network coding based evolutionary network formation for dynamic wireless networks"
    - "cost efficient qos aware data acquisition point placement for advanced metering infrastructure"
    - "distributed rate allocation in inter session network coding"
    - "dynamic network formation with incomplete information"
    - "mac centered cooperation synergistic design of network coding multi packet reception and improved fairness to increase network throughput"
    - "relay selection with network coding in two way relay channels"
    - "sensor networks with random links topology design for distributed consensus"

Connected through hyperedge HE-3 (induced by source paper "distributed rate allocation in inter session network coding"):
  with members:
    - "network coding meets multimedia a review"
    - "network coding for multiple unicasts an interference alignment approach"
    - "informed network coding for minimum decoding delay"

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)