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: "number balancing is as hard as minkowski s theorem and shortest vector"
  Abstract: The number balancing (NBP) problem is the following: given real numbers $a_1,\ldots,a_n \in [0,1]$, find two disjoint subsets $I_1,I_2 \subseteq [n]$ so that the difference $|\sum_{i \in I_1}a_i - \sum_{i \in I_2}a_i|$ of their sums is minimized. An application of the pigeonhole principle shows that there is always a solution where the difference is at most $O(\frac{\sqrt{n}}{2^n})$. Finding the minimum, however, is NP-hard. In polynomial time,the differencing algorithm by Karmarkar and Karp from 1982 can produce a solution with difference at most $n^{-\Theta(\log n)}$, but no further improvement has been made since then. #R##N#In this paper, we show a relationship between NBP and Minkowski's Theorem. First we show that an approximate oracle for Minkowski's Theorem gives an approximate NBP oracle. Perhaps more surprisingly, we show that an approximate NBP oracle gives an approximate Minkowski oracle. In particular, we prove that any polynomial time algorithm that guarantees a solution of difference at most $2^{\sqrt{n}} / 2^{n}$ would give a polynomial approximation for Minkowski as well as a polynomial factor approximation algorithm for the Shortest Vector Problem.

Connected through hyperedge HE-1 (induced by source paper "equal subset sum faster than the meet in the middle"):
  with members:
    - "ppp completeness with connections to cryptography"
    - "a simple near linear pseudopolynomial time randomized algorithm for subset sum"
    - "subset sum made simple"
    - "seth based lower bounds for subset sum and bicriteria path"
    - "on problems as hard as cnf sat"
    - "a near linear pseudopolynomial time algorithm for subset sum"
    - "a faster pseudopolynomial time algorithm for subset sum"
    - "space time tradeoffs for subset sum an improved worst case algorithm"

Connected through hyperedge HE-2 (induced by source paper "balancing gaussian vectors in high dimension"):
  with members:
    - "on the discrepancy of random low degree set systems"
    - "reducibility and computational lower bounds for problems with planted sparse structure"
    - "near linear time approximation algorithms for optimal transport via sinkhorn iteration"
    - "deterministic discrepancy minimization via the multiplicative weight update method"
    - "constructive discrepancy minimization for convex sets"
    - "constructive algorithms for discrepancy minimization"
    - "analysis of the karmarkar karp differencing algorithm"

Connected through hyperedge HE-3 (induced by source paper "ppp completeness with connections to cryptography"):
  with members:
    - "on the polynomial parity argument complexity of the combinatorial nullstellensatz"
    - "consensus halving is ppa complete"
    - "cls new problems and completeness"
    - "a converse to banach s fixed point theorem and its cls completeness"
    - "local max cut in smoothed polynomial time"
    - "integer factoring and modular square roots"
    - "settling the complexity of computing approximate two player nash equilibria"
    - "on the complexity of nash equilibria in anonymous games"

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)