human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "a tail bound for read k families of functions"
  Abstract: We prove a Chernoff-like large deviation bound on the sum of non-independent random variables that have the following dependence structure. The variables $Y_1,...,Y_r$ are arbitrary Boolean functions of independent random variables $X_1,...,X_m$, modulo a restriction that every $X_i$ influences at most $k$ of the variables $Y_1,...,Y_r$.

Connected through hyperedge HE-1 (induced by source paper "average case lower bounds and satisfiability algorithms for small threshold circuits"):
  with members:
    - "analysis of boolean functions"
    - "new algorithms and lower bounds for circuits with linear threshold gates"
    - "a satisfiability algorithm for sparse depth two threshold circuits"
    - "a satisfiability algorithm for ac 0"
    - "average sensitivity and noise sensitivity of polynomial threshold functions"
    - "bounded independence fools halfspaces"
    - "bounding the sensitivity of polynomial threshold functions"
    - "pseudorandom generators for polynomial threshold functions"

Connected through hyperedge HE-2 (induced by source paper "joint alignment from pairwise differences with a noisy oracle"):
  with members:
    - "optimal learning of joint alignments with a faulty oracle"
    - "predicting positive and negative links with noisy queries theory practice"
    - "the projected power method an efficient algorithm for joint alignment from pairwise differences"
    - "clustering via crowdsourcing"
    - "a semidefinite program for unbalanced multisection in the stochastic block model"
    - "beyond triangles a distributed framework for estimating 3 profiles of large graphs"
    - "mathematical and algorithmic analysis of network and biological data"
    - "exact recovery in the stochastic block model"

Connected through hyperedge HE-3 (induced by source paper "scalable motif aware graph clustering"):
  with members:
    - "higher order organization of complex networks"
    - "tensor spectral clustering for partitioning higher order network structures"
    - "heat kernel based community detection"
    - "hypergraph markov operators eigenvalues and approximation algorithms"
    - "using triangles to improve community detection in directed networks"
    - "parallel triangle counting in massive streaming graphs"
    - "a space efficient streaming algorithm for triangle counting using the birthday paradox"
    - "defining and evaluating network communities based on ground truth"

Connected through hyperedge HE-4 (induced by source paper "using read k inequalities to analyze a distributed mis algorithm"):
  with members:
    - "an improved distributed algorithm for maximal independent set"
    - "the locality of distributed symmetry breaking"

Connected through hyperedge HE-5 (induced by source paper "distributed estimation of graph 4 profiles"):
  with members:
    - "clique counting in mapreduce algorithms and experiments"
    - "approximately counting triangles in sublinear time"
    - "beyond triangles a distributed framework for estimating 3 profiles of large graphs"
    - "path sampling a fast and provable method for estimating 4 vertex subgraph counts"
    - "graph sample and hold a framework for big graph analytics"
    - "triadic measures on graphs the power of wedge sampling"
    - "subgraph frequencies mapping the empirical and extremal geography of large graph collections"
    - "identifying discriminating network motifs in youtube spam"

Question: Please tell me which class the center node 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)