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: "conditional lower bound for rna folding problem"
  Abstract: An RNA sequence is a string composed of four types of nucleotides, $A, C, G$, and $U$. Given an RNA sequence, the goal of the RNA folding problem is to find a maximum cardinality set of crossing-free pairs of the form $\{A,U\}$ or $\{C,G\}$. The problem is central in bioinformatics and has received much attention over the years. However, the current best algorithm for the problem still takes $\mathcal{O}\left(\frac{n^3}{\log^2 (n)}\right)$ time, which is only a slight improvement over the classic $\mathcal{O}(n^3)$ dynamic programming algorithm. Whether the RNA folding problem can be solved in $\mathcal{O}(n^{3-\epsilon})$ time remains an open problem. Recently, Abboud, Backurs, and Williams (FOCS'15) made the first progress by showing a conditional lower bound for a generalized version of the RNA folding problem based on a conjectured hardness of the $k$-clique problem. A drawback of their work is that they require the RNA sequence to have at least 36 types of letters, making their result biologically irrelevant. In this paper, we show that by constructing the gadgets using a powerful lemma of Bringmann and K\"unnemann (FOCS'15) and surrounding them with some carefully designed sequences, the framework of Abboud et al. can be improved upon to work for the case where the alphabet size is 4, yielding a conditional lower bound for the RNA folding problem.

Connected through hyperedge HE-1 (induced by source paper "fine grained complexity of analyzing compressed data quantifying improvements over decompress and solve"):
  with members:
    - "truly sub cubic algorithms for language edit distance and rna folding via fast bounded difference min plus product"
    - "why is it hard to beat o n 2 for longest common weakly increasing subsequence"
    - "a dichotomy for regular expression membership testing"
    - "the k mismatch problem revisited"
    - "clustered integer 3sum via additive combinatorics"
    - "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"
    - "if the current clique algorithms are optimal so is valiant s parser"

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)