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: "low density lattice codes"
  Abstract: Low density lattice codes (LDLC) are novel lattice codes that can be decoded efficiently and approach the capacity of the additive white Gaussian noise (AWGN) channel. In LDLC a codeword x is generated directly at the n-dimensional Euclidean space as a linear transformation of a corresponding integer message vector b, i.e., x = Gb, where H, the inverse of G, is restricted to be sparse. The fact that H is sparse is utilized to develop a linear-time iterative decoding scheme which attains, as demonstrated by simulations, good error performance within ~0.5dB from capacity at block length of n = 100,000 symbols. The paper also discusses convergence results and implementation considerations.

Connected through hyperedge HE-1 (induced by source paper "neural fuzzy extractors a secure way to use artificial neural networks for biometric user authentication"):
  with members:
    - "fingerprints fixed length representation via deep networks and domain knowledge"
    - "in defense of the triplet loss for person re identification"
    - "fingernet an unified deep network for fingerprint minutiae extraction"
    - "deep image retrieval learning global representations for image search"
    - "deep compression compressing deep neural networks with pruning trained quantization and huffman coding"
    - "facenet a unified embedding for face recognition and clustering"
    - "deep representations for iris face and fingerprint spoofing detection"
    - "very deep convolutional networks for large scale image recognition"

Connected through hyperedge HE-2 (induced by source paper "on the decoding of barnes wall lattices"):
  with members:
    - "multilevel constructions coding packing and geometric uniformity"
    - "soft decision decoding of reed muller codes recursive lists"
    - "finite dimensional infinite constellations"
    - "turbo lattices construction and error decoding performance"
    - "practical encoders and decoders for euclidean codes from barnes wall lattices"
    - "list decoding barnes wall lattices"

Connected through hyperedge HE-3 (induced by source paper "lattice coding for downlink multiuser transmission"):
  with members:
    - "downlink non orthogonal multiple access without sic for block fading channels an algebraic rotation approach"
    - "joint pilot and payload power control for uplink mimo noma with mrc sic receivers"
    - "short packet downlink transmission with non orthogonal multiple access"
    - "a multi beam noma framework for hybrid mmwave systems"
    - "optimal resource allocation for power efficient mc noma with imperfect channel state information"
    - "improved decoding and error floor analysis of staircase codes"
    - "performance analysis of a hybrid downlink uplink cooperative noma scheme"
    - "on non orthogonal multiple access with finite alphabet inputs in z channels"

Connected through hyperedge HE-4 (induced by source paper "sparse regression codes"):
  with members:
    - "the error probability of sparse superposition codes with approximate message passing decoding"
    - "sparcs for unsourced random access"
    - "spatially coupled sparse regression codes design and state evolution analysis"
    - "techniques for improving the finite length performance of sparse superposition codes"
    - "approximate message passing decoder and capacity achieving sparse superposition codes"
    - "capacity achieving sparse superposition codes via approximate message passing decoding"
    - "the rate distortion function and excess distortion exponent of sparse regression codes with optimal encoding"
    - "universal sparse superposition codes with spatial coupling and gamp decoding"

Connected through hyperedge HE-5 (induced by source paper "ratq a universal fixed length quantizer for stochastic optimization"):
  with members:
    - "error feedback fixes signsgd and other gradient compression schemes"
    - "nuqsgd improved communication efficiency for data parallel sgd via nonuniform quantization"
    - "inference under information constraints ii communication constraints and shared randomness"
    - "vqsgd vector quantized stochastic gradient descent"
    - "distributed learning with sublinear communication"
    - "open problem the oracle complexity of convex optimization with limited memory"
    - "geometric lower bounds for distributed parameter estimation under communication constraints"
    - "sparsified sgd with memory"

Connected through hyperedge HE-6 (induced by source paper "potential key technologies for 6g mobile communications"):
  with members:
    - "6g the next frontier"
    - "enabling large intelligent surfaces with compressive sensing and deep learning"
    - "beyond massive mimo the potential of data transmission with large intelligent surfaces"
    - "low complexity receiver for uplink scma system via expectation propagation"
    - "the potential of using large antenna arrays on intelligent surfaces"

Connected through hyperedge HE-7 (induced by source paper "a lattice based joint encryption encoding and modulation scheme"):
  with members:
    - "ldpc lattice codes for full duplex relay channels"
    - "on the performance of 1 level ldpc lattices"

Connected through hyperedge HE-8 (induced by source paper "neural lattice decoders"):
  with members:
    - "a neural network lattice decoding algorithm"
    - "leech constellations of construction a lattices"
    - "learning to decode linear codes using deep learning"
    - "construction of capacity achieving lattice codes polar lattices"

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)