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 "tighter connections between formula sat and shaving logs"):
  Abstract: A noticeable fraction of Algorithms papers in the last few decades improve the running time of well-known algorithms for fundamental problems by logarithmic factors. For example, the $O(n^2)$ dynamic programming solution to the Longest Common Subsequence problem (LCS) was improved to $O(n^2/\log^2 n)$ in several ways and using a variety of ingenious tricks. This line of research, also known as "the art of shaving log factors", lacks a tool for proving negative results. Specifically, how can we show that it is unlikely that LCS can be solved in time $O(n^2/\log^3 n)$? #R##N#Perhaps the only approach for such results was suggested in a recent paper of Abboud, Hansen, Vassilevska W. and Williams (STOC'16). The authors blame the hardness of shaving logs on the hardness of solving satisfiability on Boolean formulas (Formula-SAT) faster than exhaustive search. They show that an $O(n^2/\log^{1000} n)$ algorithm for LCS would imply a major advance in circuit lower bounds. Whether this approach can lead to tighter barriers was unclear. #R##N#In this paper, we push this approach to its limit and, in particular, prove that a well-known barrier from complexity theory stands in the way for shaving five additional log factors for fundamental combinatorial problems. For LCS, regular expression pattern matching, as well as the Fr\'echet distance problem from Computational Geometry, we show that an $O(n^2/\log^{7+\varepsilon} n)$ runtime would imply new Formula-SAT algorithms. #R##N#Our main result is a reduction from SAT on formulas of size $s$ over $n$ variables to LCS on sequences of length $N=2^{n/2} \cdot s^{1+o(1)}$. Our reduction is essentially as efficient as possible, and it greatly improves the previously known reduction for LCS with $N=2^{n/2} \cdot s^c$, for some $c \geq 100$.

Includes members:
  Member "subquadratic algorithms for succinct stable matching":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "more consequences of falsifying seth and the orthogonal vectors conjecture")
  Member "a dichotomy for regular expression membership testing":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "more consequences of falsifying seth and the orthogonal vectors conjecture")
  Member "an improved combinatorial algorithm for boolean matrix multiplication":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "engineering boolean matrix multiplication for multiple accelerator shared memory architectures")
  Member "improved bounds for 3sum k sum and linear degeneracy":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "all non trivial variants of 3 ldt are equivalent")
  Member "fr echet distance for curves revisited":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a fast implementation of near neighbors queries for frechet distance gis cup")
  Member "subtree isomorphism revisited":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "faster approximation algorithms for computing shortest cycles on weighted graphs")
  Member "which regular expression patterns are hard to match":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "graphs cannot be indexed in polynomial time for sub quadratic time string matching unless seth fails")
  Member "simulating branching programs with edit distance and friends or a polylog shaved is a lower bound made":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "streaming with oracle new streaming algorithms for edit distance and lcs")

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.CC(Computational Complexity)