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 "dynamic programming for sequential deterministic quantization of discrete memoryless channels"):
  Abstract: In this paper, under a general cost function, we present a dynamic programming (DP) method to obtain an optimal sequential deterministic quantizer (SDQ) for $q$-ary input discrete memoryless channel (DMC). The DP method has complexity $O(q (N-M)^2 M)$, where $N$ and $M$ are the alphabet sizes of the DMC output and quantizer output, respectively. Then, starting from the quadrangle inequality (QI), two techniques are applied to reduce the DP method's complexity. One technique makes use of the SMAWK algorithm and achieves complexity $O(q (N-M) M)$. The other technique is much easier to be implemented and achieves complexity $O(q (N^2 - M^2))$. We further derive a sufficient condition under which the optimal SDQ is optimal among all quantizers and the two techniques are also applicable. This generalizes the results in the literature for binary-input DMC. Next, we show that the cost function of $\alpha$-mutual information ($\alpha$-MI)-maximizing quantizer belongs to the general cost function we adopt earlier. We further prove that under a weaker condition than the sufficient condition we derived, the aforementioned two techniques are applicable to the design of $\alpha$-MI-maximizing quantizer. Finally, we propose a new algorithm called iterative DP (IDP). Theoretical analysis and simulation results demonstrate that IDP can improve the quantizer design over the state-of-the-art methods in the literature.

Includes members:
  Member "mutual information maximizing quantized belief propagation decoding of ldpc codes":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "dynamic programming for discrete memoryless channel quantization")
  Member "information theoretic bounds based channel quantization design for emerging memories":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "deep learning aided dynamic read thresholds design for multi level cell flash memories")
  Member "enhanced precision through multiple reads for ldpc decoding in flash memories":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a combinatorial methodology for optimizing non binary graph based codes theoretical analysis and applications in data storage")
  Member "how to construct polar codes":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "polar codes and their quantum domain counterparts")
  Member "quantization of binary input discrete memoryless channels":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "intelligence physics and information the tradeoff between accuracy and simplicity in machine learning")

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)