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: "prefix codes equiprobable words unequal letter costs"
  Abstract: We consider the following variant of Huffman coding in which the costs of the letters, rather than the probabilities of the words, are nonuniform: ``Given an alphabet of $r$ letters {\em of nonuniform length}, find a minimum-average-length prefix-free set of $n$ codewords over the alphabet''; equivalently, ``Find an optimal $r$-ary search tree with $n$ leaves, where each leaf is accessed with equal probability but the cost to descend from a parent to its $i$th child depends on $i$.'' We show new structural properties of such codes, leading to an $O(n\log^2 r)$-time algorithm for finding them. This new algorithm is simpler and faster than the best previously known $O(nr\, \min\{\log n, r\})$-time algorithm, due to Perl, Garey, and Even [{\em J. Assoc. Comput. Mach.}, 22 (1975), pp. 202--214].

Connected through hyperedge HE-1 (induced by source paper "prefix free code distribution matching for probabilistic constellation shaping"):
  with members:
    - "shell mapping for distribution matching"
    - "divergence optimal fixed to fixed length distribution matching with shell mapping"
    - "divergence scaling of fixed length binary output one to one distribution matching"
    - "fixed to variable length resolution coding for target distributions"
    - "constellation shaping for bit interleaved ldpc coded apsk"
    - "matching dyadic distributions to channels"

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.DS(Data Structures and Algorithms)