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: "approximate message passing decoder and capacity achieving sparse superposition codes"
  Abstract: We study the approximate message-passing decoder for sparse superposition coding on the additive white Gaussian noise channel and extend our preliminary work. We use heuristic statistical-physics-based tools, such as the cavity and the replica methods, for the statistical analysis of the scheme. While superposition codes asymptotically reach the Shannon capacity, we show that our iterative decoder is limited by a phase transition similar to the one that happens in low density parity check codes. We consider two solutions to this problem, that both allow to reach the Shannon capacity: 1) a power allocation strategy and 2) the use of spatial coupling, a novelty for these codes that appears to be promising. We present, in particular, simulations, suggesting that spatial coupling is more robust and allows for better reconstruction at finite code lengths. Finally, we show empirically that the use of a fast Hadamard-based operator allows for an efficient reconstruction, both in terms of computational time and memory, and the ability to deal with very large messages.

Connected through hyperedge HE-1 (induced by source paper "capacity achieving spatially coupled sparse superposition codes with amp decoding"):
  with members:
    - "sparse regression codes"
    - "the error probability of sparse superposition codes with approximate message passing decoding"
    - "spatially coupled sparse regression codes design and state evolution analysis"
    - "finite sample analysis of approximate message passing algorithms"
    - "techniques for improving the finite length performance of sparse superposition codes"
    - "capacity achieving sparse superposition codes via approximate message passing decoding"
    - "universal sparse superposition codes with spatial coupling and gamp decoding"
    - "phase transitions and sample complexity in bayes optimal matrix factorization"

Connected through hyperedge HE-2 (induced by source paper "compressed coding amp based decoding and analog spatial coupling"):
  with members:
    - "analysis of approximate message passing with non separable denoisers and markov random field priors"
    - "capacity achieving sparse superposition codes via approximate message passing decoding"
    - "universal sparse superposition codes with spatial coupling and gamp decoding"
    - "state evolution for approximate message passing with non separable functions"
    - "generalized approximate message passing decoder for universal sparse superposition codes"
    - "threshold saturation of spatially coupled sparse superposition codes for all memoryless channels"
    - "spatially coupled ldpc codes constructed from protographs"
    - "approximate message passing with spatially coupled structured operators with applications to compressed sensing and sparse superposition codes"

Connected through hyperedge HE-3 (induced by source paper "unsourced multiuser sparse regression codes achieve the symmetric mac capacity"):
  with members:
    - "grant free massive random access with a massive mimo receiver"
    - "sparse regression codes"
    - "non bayesian activity detection large scale fading coefficient estimation and unsourced random access with a massive mimo receiver"
    - "polar coding and random spreading for unsourced multiple access"
    - "capacity achieving sparse superposition codes via approximate message passing decoding"
    - "state evolution for approximate message passing with non separable functions"
    - "mutual information and optimality of approximate message passing in random linear estimation"
    - "the replica symmetric prediction for compressed sensing with gaussian matrices is exact"

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"
    - "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"
    - "threshold saturation of spatially coupled sparse superposition codes for all memoryless channels"

Connected through hyperedge HE-5 (induced by source paper "optimal errors and phase transitions in high dimensional generalized linear models"):
  with members:
    - "rethinking generalization requires revisiting old ideas statistical mechanics approaches and complex learning behavior"
    - "information theoretic thresholds from the cavity method"
    - "the layered structure of tensor estimation and its mutual information"
    - "capacity achieving sparse superposition codes via approximate message passing decoding"
    - "opening the black box of deep neural networks via information"
    - "universal sparse superposition codes with spatial coupling and gamp decoding"
    - "structured signal recovery from quadratic measurements breaking sample complexity barriers via nonconvex optimization"
    - "mutual information and optimality of approximate message passing in random linear estimation"

Connected through hyperedge HE-6 (induced by source paper "non bayesian activity detection large scale fading coefficient estimation and unsourced random access with a massive mimo receiver"):
  with members:
    - "improved scaling law for activity detection in massive mimo systems"
    - "on the fly large scale channel gain estimation for massive antenna array base stations"
    - "techniques for improving the finite length performance of sparse superposition codes"
    - "on the restricted isometry of the columnwise khatri rao product"
    - "sparse activity detection for massive connectivity"
    - "massive connectivity with massive mimo part ii achievable rate characterization"
    - "sparse signal processing for grant free massive connectivity a future paradigm for random access protocols in the internet of things"
    - "massive connectivity with massive mimo part i device activity detection and channel estimation"

Connected through hyperedge HE-7 (induced by source paper "capacity optimality of amp in coded systems"):
  with members:
    - "capacity achieving mimo noma iterative lmmse detection"
    - "a unified framework of state evolution for message passing algorithms"
    - "optimal data detection in large mimo"
    - "near gaussian multiple access channel capacity detection and decoding"
    - "capacity achieving sparse superposition codes via approximate message passing decoding"
    - "mutual information and optimality of approximate message passing in random linear estimation"
    - "compressive phase retrieval via generalized approximate message passing"
    - "compressed sensing via universal denoising and approximate message passing"

Connected through hyperedge HE-8 (induced by source paper "sparcs for unsourced random access"):
  with members:
    - "massive mimo unsourced random access"
    - "techniques for improving the finite length performance of sparse superposition codes"
    - "sparse signal processing for grant free massive iot connectivity"
    - "capacity achieving sparse superposition codes via approximate message passing decoding"
    - "on or many access channels"
    - "device activity and embedded information bit detection using amp in massive mimo"
    - "state evolution for approximate message passing with non separable functions"
    - "mutual information and optimality of approximate message passing in random linear estimation"

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)