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: "capacity achieving ensembles for the binary erasure channel with bounded complexity"
  Abstract: We present two sequences of ensembles of nonsystematic irregular repeat-accumulate (IRA) codes which asymptotically (as their block length tends to infinity) achieve capacity on the binary erasure channel (BEC) with bounded complexity per information bit. This is in contrast to all previous constructions of capacity-achieving sequences of ensembles whose complexity grows at least like the log of the inverse of the gap (in rate) to capacity. The new bounded complexity result is achieved by puncturing bits, and allowing in this way a sufficient number of state nodes in the Tanner graph representing the codes. We derive an information-theoretic lower bound on the decoding complexity of randomly punctured codes on graphs. The bound holds for every memoryless binary-input output-symmetric (MBIOS) channel and is refined for the binary erasure channel.

Connected through hyperedge HE-1 (induced by source paper "log logarithmic time pruned polar coding"):
  with members:
    - "polar like codes and asymptotic tradeoff among block length code rate and error probability"
    - "polar codes with exponentially small error at finite block length"
    - "general strong polarization"
    - "polar code moderate deviation recovering the scaling exponent"
    - "scaling exponent and moderate deviations asymptotics of polar codes for the awgn channel"
    - "relaxed polar codes"
    - "flexible length polar codes through graph based augmentation"
    - "a packing lemma for polar codes"

Connected through hyperedge HE-2 (induced by source paper "efficient error correcting codes in the short blocklength regime"):
  with members:
    - "low complexity joint channel estimation and list decoding of short codes"
    - "low latency short packet transmissions fixed length or harq"
    - "design of polar codes in 5g new radio"
    - "joint design of convolutional code and crc under serial list viterbi decoding"
    - "on the error probability of short concatenated polar and cyclic codes with interleaving"
    - "short packets over block memoryless fading channels pilot assisted or noncoherent transmission"
    - "polar code construction for list decoding"
    - "ultra sparse non binary ldpc codes for probabilistic amplitude shaping"

Connected through hyperedge HE-3 (induced by source paper "multi edge type ldpc code design with g exit charts for continuous variable quantum key distribution"):
  with members:
    - "optimization of graph based codes for belief propagation decoding"
    - "the generalized area theorem and some of its consequences"
    - "density evolution thresholds and the stability condition for non binary ldpc codes"

Connected through hyperedge HE-4 (induced by source paper "lda lattices without dithering achieve capacity on the gaussian channel"):
  with members:
    - "some goodness properties of lda lattices"
    - "ldpc lattice codes for full duplex relay channels"
    - "construction of capacity achieving lattice codes polar lattices"
    - "lattices over eisenstein integers for compute and forward"
    - "achieving awgn channel capacity with lattice gaussian coding"
    - "on the performance of 1 level ldpc lattices"
    - "spatially coupled ensembles universally achieve capacity under belief propagation"
    - "turbo lattices construction and error decoding performance"

Connected through hyperedge HE-5 (induced by source paper "code design for short blocks a survey"):
  with members:
    - "coded random access applying codes on graphs to design random access protocols"
    - "reliability output decoding of tail biting convolutional codes"
    - "advanced channel coding for space mission telecommand links"
    - "five disruptive technology directions for 5g"
    - "list decoding of polar codes"
    - "threshold saturation via spatial coupling why convolutional ldpc ensembles perform so well over the bec"
    - "multiple bases belief propagation decoding of high density cyclic codes"
    - "accumulate repeat accumulate codes capacity achieving ensembles of systematic codes for the erasure channel with bounded complexity"

Connected through hyperedge HE-6 (induced by source paper "on the design of fast convergent ldpc codes for the bec an optimization approach"):
  with members:
    - "optimal rate for irregular ldpc codes in binary erasure channel"

Connected through hyperedge HE-7 (induced by source paper "a fast convergence density evolution algorithm for optimal rate ldpc codes in bec"):
  with members:
    - "optimal rate for irregular ldpc codes in binary erasure channel"
    - "channel coding the road to channel capacity"

Connected through hyperedge HE-8 (induced by source paper "optimal rate and maximum erasure probability ldpc codes in binary erasure channel"):
  with members:
    - "on universal properties of capacity approaching ldpc code ensembles"
    - "how to find good finite length codes from art towards science"

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)