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: "submodular cost allocation problem and applications"
  Abstract: We study the Minimum Submodular-Cost Allocation problem (MSCA). In this problem we are given a finite ground set $V$ and $k$ non-negative submodular set functions $f_1 ,..., f_k$ on $V$. The objective is to partition $V$ into $k$ (possibly empty) sets $A_1 ,..., A_k$ such that the sum $\sum_{i=1}^k f_i(A_i)$ is minimized. Several well-studied problems such as the non-metric facility location problem, multiway-cut in graphs and hypergraphs, and uniform metric labeling and its generalizations can be shown to be special cases of MSCA. In this paper we consider a convex-programming relaxation obtained via the Lov\'asz-extension for submodular functions. This allows us to understand several previous relaxations and rounding procedures in a unified fashion and also develop new formulations and approximation algorithms for several problems. In particular, we give a $(1.5 - 1/k)$-approximation for the hypergraph multiway partition problem. We also give a $\min\{2(1-1/k), H_{\Delta}\}$-approximation for the hypergraph multiway cut problem when $\Delta$ is the maximum hyperedge size. Both problems generalize the multiway cut problem in graphs and the hypergraph cut problem is approximation equivalent to the node-weighted multiway cut problem in graphs.

Connected through hyperedge HE-1 (induced by source paper "improved approximation algorithms for inventory problems"):
  with members:
    - "approximation algorithms for inventory problems with submodular or routing costs"
    - "local distribution and the symmetry gap approximability of multiway partitioning problems"
    - "approximation algorithms for submodular multiway partition"

Connected through hyperedge HE-2 (induced by source paper "multi agent submodular optimization"):
  with members:
    - "constrained submodular maximization via a non symmetric technique"
    - "submodular approximation sampling based algorithms and lower bounds"

Connected through hyperedge HE-3 (induced by source paper "randomized bicriteria approximation algorithm for minimum submodular cost partial multi cover problem"):
  with members:
    - "analytical approach to parallel repetition"
    - "submodular functions extensions distributions and algorithms a survey"

Connected through hyperedge HE-4 (induced by source paper "mixed robust average submodular partitioning fast algorithms guarantees and applications"):
  with members:
    - "a deterministic algorithm for maximizing submodular functions"
    - "graph partitioning via parallel submodular approximation to accelerate distributed machine learning"
    - "local distribution and the symmetry gap approximability of multiway partitioning problems"
    - "parallel training of dnns with natural gradient and parameter averaging"
    - "submodular optimization with submodular cover and submodular knapsack constraints"
    - "fast semidifferential based submodular function optimization"
    - "algorithms for approximate minimization of the difference between submodular functions with applications"
    - "approximation algorithms for submodular multiway partition"

Connected through hyperedge HE-5 (induced by source paper "simple and fast rounding algorithms for directed and node weighted multiway cut"):
  with members:
    - "computing the k nearest neighbors for all vertices via dijkstra"
    - "local distribution and the symmetry gap approximability of multiway partitioning problems"
    - "multiway cut pairwise realizable distributions and descending thresholds"
    - "multicommodity flows and cuts in polymatroidal networks"
    - "approximation algorithms for submodular multiway partition"
    - "faster approximation schemes for fractional multicommodity flow problems via dynamic graph algorithms"
    - "rounding algorithms for a geometric embedding of minimum multiway cut"
    - "randomized rounding without solving the linear program"

Connected through hyperedge HE-6 (induced by source paper "local distribution and the symmetry gap approximability of multiway partitioning problems"):
  with members:
    - "multiway cut pairwise realizable distributions and descending thresholds"
    - "the power of linear programming for valued csps"
    - "symmetry and approximability of submodular maximization problems"
    - "approximation algorithms for submodular multiway partition"
    - "rounding algorithms for a geometric embedding of minimum multiway cut"

Connected through hyperedge HE-7 (induced by source paper "approximation algorithms for connected maximum cut and related problems"):
  with members:
    - "a new perspective on vertex connectivity"
    - "analyzing the optimal neighborhood algorithms for budgeted and partial connected dominating set problems"
    - "deterministic parameterized connected vertex cover"

Connected through hyperedge HE-8 (induced by source paper "maximizing symmetric submodular functions"):
  with members:
    - "constrained submodular maximization via a non symmetric technique"
    - "constrained submodular maximization beyond 1 e"
    - "improved approximation algorithms for k submodular function maximization"
    - "deterministic algorithms for submodular maximization problems"
    - "local distribution and the symmetry gap approximability of multiway partitioning problems"
    - "on the approximation of submodular functions"
    - "symmetry and approximability of submodular maximization problems"
    - "approximation algorithms for submodular multiway partition"

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.DS(Data Structures and Algorithms)