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 "query complexity of sampling and small geometric partitions"):
  Abstract: In this paper we study the following problem: #R##N#Discrete partitioning problem (DPP): Let $\mathbb{F}_q P^n$ denote the $n$-dimensional finite projective space over $\mathbb{F}_q$. For positive integer $k \leq n$, let $\{ A^i\}_{i=1}^N$ be a partition of $(\mathbb{F}_q P^n)^k$ such that #R##N#(1) for all $i \leq N$, $A^i = \prod_{j=1}^k A^i_j$ (partition into product sets), #R##N#(2) for all $i \leq N$, there is a $(k-1)$-dimensional subspace $L^i \subseteq \mathbb{F}_q P^n$ such that $A^i \subseteq (L^i)^k$. #R##N#What is the minimum value of $N$ as a function of $q,n,k$? We will be mainly interested in the case $k=n$.

Includes members:
  Member "an optimal lower bound on the communication complexity of gap hamming distance":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "approximate mathbb f _2 sketching of valuation functions")
  Member "the partition bound for classical communication complexity and query complexity":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "query to communication lifting using low discrepancy gadgets")
  Member "dispersion of mass and the complexity of randomized geometric algorithms":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "estimating normalizing constants for log concave distributions algorithms and lower bounds")

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)