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: "improving viterbi is hard better runtimes imply faster clique algorithms"
  Abstract: The classic algorithm of Viterbi computes the most likely path in a Hidden Markov Model (HMM) that results in a given sequence of observations. It runs in time $O(Tn^2)$ given a sequence of $T$ observations from a HMM with $n$ states. Despite significant interest in the problem and prolonged effort by different communities, no known algorithm achieves more than a polylogarithmic speedup. #R##N#In this paper, we explain this difficulty by providing matching conditional lower bounds. We show that the Viterbi algorithm runtime is optimal up to subpolynomial factors even when the number of distinct observations is small. Our lower bounds are based on assumptions that the best known algorithms for the All-Pairs Shortest Paths problem (APSP) and for the Max-Weight $k$-Clique problem in edge-weighted graphs are essentially tight. #R##N#Finally, using a recent algorithm by Green Larsen and Williams for online Boolean matrix-vector multiplication, we get a $2^{\Omega(\sqrt {\log n})}$ speedup for the Viterbi algorithm when there are few distinct transition probabilities in the HMM.

Connected through hyperedge HE-1 (induced by source paper "graphs cannot be indexed in polynomial time for sub quadratic time string matching unless seth fails"):
  with members:
    - "regular languages meet prefix sorting"
    - "on prefix sorting finite automata"
    - "on the hardness and inapproximability of recognizing wheeler graphs"
    - "on the hardness of set disjointness and set intersection with bounded universe"
    - "lower bounds for text indexing with mismatches and differences"
    - "indexing variation graphs"
    - "distributed pcp theorems for hardness of approximation in p"
    - "the gremlin graph traversal machine and language invited talk"

Connected through hyperedge HE-2 (induced by source paper "more consequences of falsifying seth and the orthogonal vectors conjecture"):
  with members:
    - "on the fine grained complexity of empirical risk minimization kernel methods and neural networks"
    - "conditional lower bounds for all pairs max flow"
    - "on the fine grained complexity of one dimensional dynamic programming"
    - "distributed pcp theorems for hardness of approximation in p"
    - "tree edit distance cannot be computed in strongly subcubic time unless apsp can"
    - "fine grained complexity of analyzing compressed data quantifying improvements over decompress and solve"
    - "on the hardness of partially dynamic graph problems and connections to diameter"
    - "tight hardness results for maximum weight rectangles"

Connected through hyperedge HE-3 (induced by source paper "online markov decoding lower bounds and near optimal approximation algorithms"):
  with members:
    - "learning small predictors"
    - "decoding hidden markov models faster than viterbi via online matrix vector max multiplication"
    - "learning as search optimization approximate large margin methods for structured prediction"
    - "on line viterbi algorithm for analysis of long biological sequences"

Connected through hyperedge HE-4 (induced by source paper "voronoi diagrams on planar graphs and computing the diameter in deterministic tilde o n 5 3 time"):
  with members:
    - "fast and compact exact distance oracle for planar graphs"
    - "tree edit distance cannot be computed in strongly subcubic time unless apsp can"
    - "subquadratic algorithms for the diameter and the sum of pairwise distances in planar graphs"
    - "popular conjectures as a barrier for dynamic planar graph algorithms"
    - "optimal parameterized algorithms for planar facility location problems using voronoi diagrams"
    - "popular conjectures imply strong lower bounds for dynamic problems"
    - "exact weight subgraphs and the k sum conjecture"
    - "faster all pairs shortest paths via circuit complexity"

Connected through hyperedge HE-5 (induced by source paper "tight conditional lower bounds for longest common increasing subsequence"):
  with members:
    - "on problems equivalent to min convolution"
    - "multivariate fine grained complexity of longest common subsequence"
    - "why is it hard to beat o n 2 for longest common weakly increasing subsequence"
    - "on the fine grained complexity of one dimensional dynamic programming"
    - "a simple linear space algorithm for computing a longest common increasing subsequence"
    - "which regular expression patterns are hard to match"
    - "simulating branching programs with edit distance and friends or a polylog shaved is a lower bound made"
    - "quadratic conditional lower bounds for string problems and dynamic time warping"

Connected through hyperedge HE-6 (induced by source paper "tree edit distance cannot be computed in strongly subcubic time unless apsp can"):
  with members:
    - "popular conjectures as a barrier for dynamic planar graph algorithms"
    - "a near linear pseudopolynomial time algorithm for subset sum"
    - "which regular expression patterns are hard to match"

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.CC(Computational Complexity)