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: "achievable rates for probabilistic shaping"
  Abstract: For a layered probabilistic shaping (PS) scheme with a general decoding metric, an achievable rate is derived using Gallager's error exponent approach and the concept of achievable code rates is introduced. Several instances for specific decoding metrics are discussed, including bit-metric decoding, interleaved coded modulation, and hard-decision decoding. It is shown that important previously known achievable rates can also be achieved by layered PS. A practical instance of layered PS is the recently proposed probabilistic amplitude shaping (PAS).

Connected through hyperedge HE-1 (induced by source paper "achievable information rates for probabilistic amplitude shaping a minimum randomness approach via random sign coding arguments"):
  with members:
    - "information rates and error exponents for probabilistic amplitude shaping"
    - "achievable rates for shaped bit metric decoding"
    - "probabilistic signal shaping for bit metric decoding"

Connected through hyperedge HE-2 (induced by source paper "on product codes with probabilistic amplitude shaping for high throughput fiber optic systems"):
  with members:
    - "binary message passing decoding of product codes based on generalized minimum distance decoding"
    - "binary message passing decoding of product like codes"
    - "iterative bounded distance decoding of product codes with scaled reliability"
    - "on low complexity decoding of product codes for high throughput fiber optic systems"
    - "energy efficient soft assisted product decoders"
    - "increasing achievable information rates via geometric shaping"
    - "miscorrection free decoding of staircase codes"
    - "probabilistic amplitude shaping with hard decision decoding and staircase codes"

Connected through hyperedge HE-3 (induced by source paper "optimization of bit mapping and quantized decoding for off the shelf protograph ldpc codes with application to ieee 802 3ca"):
  with members:
    - "protograph based ldpc code design for shaped bit metric decoding"
    - "constant composition distribution matching"
    - "optimized bit mappings for spatially coupled ldpc codes over parallel binary erasure channels"
    - "improving soft fec performance for higher order modulations via optimized bit channel mappings"
    - "staircase codes fec for 100 gb s otn"

Connected through hyperedge HE-4 (induced by source paper "information rates and error exponents for probabilistic amplitude shaping"):
  with members:
    - "comparison of geometric and probabilistic shaping with application to atsc 3 0"
    - "optimal quantization for distribution synthesis"
    - "on probabilistic shaping of quadrature amplitude modulation for the nonlinear fiber channel"
    - "constant composition distribution matching"
    - "informational divergence and entropy rate on rooted trees with probabilities"

Connected through hyperedge HE-5 (induced by source paper "a mismatched joint source channel coding perspective of probabilistic amplitude shaping achievable rates and error exponents"):
  with members:
    - "comparison of geometric and probabilistic shaping with application to atsc 3 0"
    - "optimal quantization for distribution synthesis"
    - "on probabilistic shaping of quadrature amplitude modulation for the nonlinear fiber channel"
    - "constant composition distribution matching"

Connected through hyperedge HE-6 (induced by source paper "probabilistically shaped multi level coding with polar codes for fading channels"):
  with members:
    - "polar codes with integrated probabilistic shaping for 5g new radio"
    - "ultra sparse non binary ldpc codes for probabilistic amplitude shaping"
    - "how to achieve the capacity of asymmetric channels"
    - "list decoding of polar codes"

Connected through hyperedge HE-7 (induced by source paper "experimental verification of rate flexibility and probabilistic shaping by 4d signaling"):
  with members:
    - "experimental comparison of probabilistic shaping methods for unrepeated fiber transmission"
    - "on probabilistic shaping of quadrature amplitude modulation for the nonlinear fiber channel"
    - "constant composition distribution matching"

Connected through hyperedge HE-8 (induced by source paper "bit metric decoding of non binary ldpc codes with probabilistic amplitude shaping"):
  with members:
    - "code design for short blocks a survey"
    - "constant composition distribution matching"

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)