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 "derandomized graph product results using the low degree long code"):
  Abstract: In this paper, we address the question of whether the recent derandomization results obtained by the use of the low-degree long code can be extended to other product settings. We consider two settings: (1) the graph product results of Alon, Dinur, Friedgut and Sudakov [GAFA, 2004] and (2) the "majority is stablest" type of result obtained by Dinur, Mossel and Regev [SICOMP, 2009] and Dinur and Shinkar [In Proc. APPROX, 2010] while studying the hardness of approximate graph coloring.#R##N##R##N#In our first result, we show that there exists a considerably smaller#R##N#subgraph of K_3^{\otimes R} which exhibits the following property#R##N#(shown for K_3^{\otimes R} by Alon et al.): independent sets close in#R##N#size to the maximum independent set are well approximated by dictators.#R##N##R##N#The "majority is stablest" type of result of Dinur et al. and Dinur#R##N#and Shinkar shows that if there exist two sets of vertices A and B#R##N#in K_3^{\otimes R} with very few edges with one endpoint in A and#R##N#another in B, then it must be the case that the two sets A and B#R##N#share a single influential coordinate. In our second result, we show#R##N#that a similar "majority is stablest" statement holds good for a#R##N#considerably smaller subgraph of K_3^{\otimes R}. Furthermore using#R##N#this result, we give a more efficient reduction from Unique Games#R##N#to the graph coloring problem, leading to improved hardness  of#R##N#approximation results for coloring.

Includes members:
  Member "super polylogarithmic hypergraph coloring hardness via low degree long codes":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "quasi polynomial algorithms for list coloring of nearly intersecting hypergraphs")
  Member "reducing uniformity in khot saket hypergraph coloring hardness reductions":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "simplified inpproximability of hypergraph coloring via t agreeing families")
  Member "a prg for lipschitz functions of polynomials with applications to sparsest cut":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "approximating sparsest cut in low rank graphs via embeddings from approximately low dimensional spaces")
  Member "making the long code shorter with applications to the unique games conjecture":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "boolean functions on high dimensional expanders")
  Member "bounded independence fools halfspaces":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "list decodable subspace recovery via sum of squares")
  Member "pseudorandom generators for polynomial threshold functions":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "degree d chow parameters robustly determine degree d ptfs and algorithmic applications")
  Member "conditional hardness for approximate coloring":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "the generalized orthogonality dimension of generalized kneser graphs bounds and applications")

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)