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 "new algorithms for k degenerate graphs"):
  Abstract: A graph is $k$-degenerate if any induced subgraph has a vertex of degree at most $k$. In this paper we prove new algorithms for cliques and similar structures for these graphs. We design linear time Fixed-Parameter Tractable algorithms for induced and non induced bicliques. We prove an algorithm listing all maximal bicliques in time $\mathcal{O}(k^{3}(n-k)2^{k})$, improving the result of [D. Eppstein, Arboricity and bipartite subgraph listing algorithms, Information Processing Letters, (1994)]. We construct an algorithm listing all cliques of size $l$ in time $\mathcal{O}(l(n-k)k(k-1)^{l-2})$, improving a result of [N. Chiba and T. Nishizeki, Arboricity and subgraph listing algorithms, SIAM, (1985)]. As a consequence we can list all triangles in such graphs in time $\mathcal{O}((n-k)k^{2})$ improving the previous bound of $\mathcal{O}(nk^2)$. We show another optimal algorithm listing all maximal cliques in time $\mathcal{O}(k(n-k)3^{k/3})$, matching the best possible complexity proved in [D. Eppstein, M. L\"offler, and D. Strash, Listing all maximal cliques in large sparse real-world graphs, JEA, (2013)]. Finally we prove $(2-\frac{1}{k})$ and $\mathcal{O}(k(\log\log k)^{2}\slash (\log k)^{3})$-approximation algorithms for the minimum vertex cover and the maximum clique problems, respectively.

Includes members:
  Member "listing all maximal cliques in sparse graphs in near optimal time":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "teaser fast and certifiable point cloud registration")
  Member "an o m algorithm for cores decomposition of networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "fastgae fast scalable and effective graph autoencoders with stochastic subgraph decoding")

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.DM(Discrete Mathematics)