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: "why block length and delay behave differently if feedback is present"
  Abstract: For output-symmetric DMCs at even moderately high rates, fixed-block-length communication systems show no improvements in their error exponents with feedback. In this paper, we study systems with fixed end-to-end delay and show that feedback generally provides dramatic gains in the error exponents. #R##N#A new upper bound (the uncertainty-focusing bound) is given on the probability of symbol error in a fixed-delay communication system with feedback. This bound turns out to have a similar form to Viterbi's bound used for the block error probability of convolutional codes as a function of the fixed constraint length. The uncertainty-focusing bound is shown to be asymptotically achievable with noiseless feedback for erasure channels as well as any output-symmetric DMC that has strictly positive zero-error capacity. Furthermore, it can be achieved in a delay-universal (anytime) fashion even if the feedback itself is delayed by a small amount. Finally, it is shown that for end-to-end delay, it is generally possible at high rates to beat the sphere-packing bound for general DMCs -- thereby providing a counterexample to a conjecture of Pinsker.

Connected through hyperedge HE-1 (induced by source paper "symbol index feedback polar coding schemes for low complexity devices"):
  with members:
    - "channel polarization a method for constructing capacity achieving codes for symmetric binary input memoryless channels"

Connected through hyperedge HE-2 (induced by source paper "diversity embedded streaming erasure codes de sco constructions and optimality"):
  with members:
    - "avoiding interruptions qoe trade offs in block coded streaming media applications"
    - "doped fountain coding for minimum delay data collection in circular networks"
    - "arq for network coding"
    - "lossless coding for distributed streaming sources"

Connected through hyperedge HE-3 (induced by source paper "the finite dimensional witsenhausen counterexample"):
  with members:
    - "wireless network information flow a deterministic approach"
    - "information embedding meets distributed control"
    - "lattice strategies for the dirty multiple access channel"
    - "the price of certainty waterslide curves and the gap to capacity"
    - "a deterministic approach to wireless relay networks"
    - "gaussian interference channel capacity to within one bit"
    - "multiaccess channels with state known to some encoders and independent messages"
    - "cognitive radio an information theoretic perspective"

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)