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 "more consequences of falsifying seth and the orthogonal vectors conjecture"):
  Abstract: The Strong Exponential Time Hypothesis and the OV-conjecture are two popular hardness assumptions used to prove a plethora of lower bounds, especially in the realm of polynomial-time algorithms. The OV-conjecture in moderate dimension states there is no e>0 for which an O(N2−e) poly(D) time algorithm can decide whether there is a pair of orthogonal vectors in a given set of size N that contains D-dimensional binary vectors.    We strengthen the evidence for these hardness assumptions. In particular, we show that if the OV-conjecture fails, then two problems for which we are far from obtaining even tiny improvements over exhaustive search would have surprisingly fast algorithms. If the OV conjecture is false, then there is a fixed e>0 such that:    - For all d and all large enough k, there is a randomized algorithm that takes O(n(1−e)k) time to solve the Zero-Weight-k-Clique and Min-Weight-k-Clique problems on d-hypergraphs with n vertices. As a consequence, the OV-conjecture is implied by the Weighted Clique conjecture.    - For all c, the satisfiability of sparse TC1 circuits on n inputs (that is, circuits with cn wires, depth clogn, and negation, AND, OR, and threshold gates) can be computed in time O((2−e)n).

Includes members:
  Member "on the fine grained complexity of empirical risk minimization kernel methods and neural networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "tight kernel query complexity of kernel ridge regression and kernel k means clustering")
  Member "conditional lower bounds for all pairs max flow":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "on two measures of distance between fully labelled trees")
  Member "on the fine grained complexity of one dimensional dynamic programming":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "on the fine grained complexity of parity problems")
  Member "distributed pcp theorems for hardness of approximation in p":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "graphs cannot be indexed in polynomial time for sub quadratic time string matching unless seth fails")
  Member "tree edit distance cannot be computed in strongly subcubic time unless apsp can":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "new algorithms and hardness for incremental single source shortest paths in directed graphs")
  Member "fine grained complexity of analyzing compressed data quantifying improvements over decompress and solve":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "fast exact dynamic time warping on run length encoded time series")
  Member "improving viterbi is hard better runtimes imply faster clique algorithms":
    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 "on the hardness of partially dynamic graph problems and connections to diameter":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "rounding dynamic matchings against an adaptive adversary")

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)