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 "the set cover conjecture and subgraph isomorphism with a tree pattern"):
  Abstract: In the Set Cover problem, the input is a ground set of $n$ elements and a collection of $m$ sets, and the goal is to find the smallest sub-collection of sets whose union is the entire ground set. The fastest algorithm known runs in time $O(mn2^n)$ [Fomin et al., WG 2004], and the Set Cover Conjecture (SeCoCo) [Cygan et al., TALG 2016] asserts that for every fixed $\varepsilon>0$, no algorithm can solve Set Cover in time $2^{(1-\varepsilon)n}poly(m)$, even if set sizes are bounded by $\Delta=\Delta(\varepsilon)$. We show strong connections between this problem and kTree, a special case of Subgraph Isomorphism where the input is an $n$-node graph $G$ and a $k$-node tree $T$, and the goal is to determine whether $G$ has a subgraph isomorphic to $T$. #R##N#First, we propose a weaker conjecture Log-SeCoCo, that allows input sets of size $\Delta=O(1/\varepsilon \cdot\log n)$, and show that an algorithm breaking Log-SeCoCo would imply a faster algorithm than the currently known $2^n poly(n)$-time algorithm [Koutis and Williams, TALG 2016] for Directed nTree, which is kTree with $k=n$ and arbitrary directions to the edges of $G$ and $T$. This would also improve the running time for Directed Hamiltonicity, for which no algorithm significantly faster than $2^n poly(n)$ is known despite extensive research. #R##N#Second, we prove that if Set Cover cannot be solved significantly faster than $2^npoly(m)$ (an assumption even weaker than Log-SeCoCo), then kTree cannot be computed significantly faster than $2^kpoly(n)$, the running time of the Koutis and Williams' algorithm. Applying the same techniques to the p-Partial Cover problem, a parameterized version of Set Cover that requires covering at least $p$ elements, we obtain a new algorithm with running time $(2+\varepsilon)^p (m+n)^{O(1/\varepsilon)}$ for arbitrary $\varepsilon>0$, which improves previous work and is nearly optimal assuming say Log-SeCoCo.

Includes members:
  Member "seth based lower bounds for subset sum and bicriteria path":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "scheduling lower bounds via and subset sum")
  Member "finding large set covers faster via the representation method":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "conditional lower bound for subgraph isomorphism with a tree pattern")
  Member "on problems as hard as cnf sat":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "coarse grained complexity for dynamic algorithms")
  Member "on the equivalence among problems of bounded width":
    also connected through other hyperedges:
      (none)
  Member "everything you always wanted to know about the parameterized complexity of subgraph isomorphism but were afraid to ask":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "almost tight lower bounds for hard cutting problems in embedded graphs")
  Member "below all subsets for some permutational counting problems":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "sfcm r a novel algorithm for the hamiltonian sequence problem")
  Member "constrained multilinear detection and generalized graph motifs":
    also connected through other hyperedges:
      (none)
  Member "narrow sieves for parameterized paths and packings":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "finding temporal patterns using algebraic fingerprints")

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.DS(Data Structures and Algorithms)