human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "hardware based admm lp decoding"):
  Abstract: In this paper we present an FPGA-based implementation of linear programming (LP) decoding. LP decoding frames error correction as an optimization problem. This is in contrast to variants of belief propagation (BP) decoding that view error correction as a problem of graphical inference. There are many advantages to taking the optimization perspective: convergence guarantees, improved performance in certain regimes, and a methodology for incorporating the latest developments in optimization techniques. However, LP decoding, when implemented with standard LP solvers, does not easily scale to the blocklengths of modern error-correction codes. In earlier work, we showed that by drawing on decomposition methods from optimization theory, specifically the alternating direction method of multipliers (ADMM), we could build an LP decoding solver that was competitive with BP, both in terms of performance and speed. We also observed empirically that LP decoders have much better high-SNR performance in the "error floor" regime, a trait of particular relevance to optical transport and storage applications. While our previous implementation was in floating point, in this paper we report initial results of a fixed-point, hardware-based realization of our ADMM-LP decoder.

Includes members:
  Member "the admm penalized decoder for ldpc codes":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "admm based decoder for binary linear codes aided by deep learning")
  Member "hardware based projection onto the parity polytope and probability simplex":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "efficient qp admm decoder for binary ldpc codes and its performance analysis")
  Member "adaptive cut generation algorithm for improved linear programming decoding of binary linear codes":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "admm based decoder for binary linear codes aided by deep learning")
  Member "decomposition methods for large scale lp decoding":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "admm based decoder for binary linear codes aided by deep learning")
  Member "adaptive methods for linear programming decoding":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "efficient qp admm decoder for binary ldpc codes and its performance analysis")
  Member "towards low complexity linear programming decoding":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "adaptive linear programming decoding of nonbinary linear codes over prime fields")

Question: Please tell me which class the source paper 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)