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: "constrained monotone function maximization and the supermodular degree"
  Abstract: The problem of maximizing a constrained monotone set function has many practical applications and generalizes many combinatorial problems. Unfortunately, it is generally not possible to maximize a monotone set function up to an acceptable approximation ratio, even subject to simple constraints. One highly studied approach to cope with this hardness is to restrict the set function. An outstanding disadvantage of imposing such a restriction on the set function is that no result is implied for set functions deviating from the restriction, even slightly. A more flexible approach, studied by Feige and Izsak, is to design an approximation algorithm whose approximation ratio depends on the complexity of the instance, as measured by some complexity measure. Specifically, they introduced a complexity measure called supermodular degree, measuring deviation from submodularity, and designed an algorithm for the welfare maximization problem with an approximation ratio that depends on this measure. #R##N#In this work, we give the first (to the best of our knowledge) algorithm for maximizing an arbitrary monotone set function, subject to a k-extendible system. This class of constraints captures, for example, the intersection of k-matroids (note that a single matroid constraint is sufficient to capture the welfare maximization problem). Our approximation ratio deteriorates gracefully with the complexity of the set function and k. Our work can be seen as generalizing both the classic result of Fisher, Nemhauser and Wolsey, for maximizing a submodular set function subject to a k-extendible system, and the result of Feige and Izsak for the welfare maximization problem. Moreover, when our algorithm is applied to each one of these simpler cases, it obtains the same approximation ratio as of the respective original work.

Connected through hyperedge HE-1 (induced by source paper "beyond submodular maximization"):
  with members:
    - "distributed maximization of submodular plus diversity functions for multi label feature selection on huge datasets"
    - "weakly submodular maximization beyond cardinality constraints does randomization help greedy"
    - "online submodular welfare maximization greedy beats 1 2 in random order"
    - "guarantees for greedy maximization of non submodular functions with applications"
    - "local search for max sum diversification"
    - "max sum diversification monotone submodular functions and semi metric spaces"
    - "max sum diversity via convex programming"
    - "building a good team secretary problems and the supermodular degree"

Connected through hyperedge HE-2 (induced by source paper "joint placement and allocation of virtual network functions with budget and capacity constraints"):
  with members:
    - "shortest path and maximum flow problems under service function chaining constraints"
    - "towards practical constrained monotone submodular maximization"
    - "optimal dynamic cloud network control"
    - "provably efficient algorithms for joint placement and allocation of virtual network functions"
    - "approximate and incremental network function placement"
    - "online admission control and embedding of service chains"

Connected through hyperedge HE-3 (induced by source paper "capturing complementarity in set functions by going beyond submodularity subadditivity"):
  with members:
    - "network essence pagerank completion and centrality conforming markov chains"
    - "simple mechanisms for agents with complements"
    - "a simple and approximately optimal mechanism for a buyer with complements"
    - "building a good team secretary problems and the supermodular degree"
    - "a unifying hierarchy of valuations with complements and substitutes"
    - "combinatorial auctions via posted prices"
    - "combinatorial auctions with restricted complements"
    - "algorithmic pricing via virtual valuations"

Connected through hyperedge HE-4 (induced by source paper "weakly submodular maximization beyond cardinality constraints does randomization help greedy"):
  with members:
    - "guarantees for greedy maximization of non submodular functions with applications"
    - "submodular variational inference for network reconstruction"
    - "why should i trust you explaining the predictions of any classifier"
    - "constrained submodular maximization via a non symmetric technique"
    - "constrained submodular maximization beyond 1 e"
    - "building a good team secretary problems and the supermodular degree"
    - "lazier than lazy greedy"
    - "maximizing symmetric submodular functions"

Connected through hyperedge HE-5 (induced by source paper "assisting service providers in peer to peer marketplaces maximizing gain over flexible attributes"):
  with members:
    - "query reranking as a service"

Connected through hyperedge HE-6 (induced by source paper "a simple and approximately optimal mechanism for a buyer with complements"):
  with members:
    - "approximate revenue maximization with multiple items"
    - "simple mechanisms for subadditive buyers via duality"
    - "the competition complexity of auctions a bulow klemperer result for multi dimensional bidders"
    - "simple mechanisms for agents with complements"
    - "mechanism design for subadditive agents via an ex ante relaxation"
    - "building a good team secretary problems and the supermodular degree"
    - "simple mechanisms for a subadditive buyer and applications to revenue monotonicity"
    - "a simple and approximately optimal mechanism for an additive buyer"

Connected through hyperedge HE-7 (induced by source paper "building a good team secretary problems and the supermodular degree"):
  with members:
    - "a unifying hierarchy of valuations with complements and substitutes"
    - "prophet inequalities with limited information"
    - "advances on matroid secretary problems free order model and laminar case"
    - "the simulated greedy algorithm for several submodular matroid secretary problems"
    - "matroid secretary problem in the random assignment model"

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)