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: "bicriteria network design problems"
  Abstract: We study a general class of bicriteria network design problems. A generic problem in this class is as follows: Given an undirected graph and two minimization objectives (under different cost functions), with a budget specified on the first, find a <subgraph \from a given subgraph-class that minimizes the second objective subject to the budget on the first. We consider three different criteria - the total edge cost, the diameter and the maximum degree of the network. Here, we present the first polynomial-time approximation algorithms for a large class of bicriteria network design problems for the above mentioned criteria. The following general types of results are presented. #R##N#First, we develop a framework for bicriteria problems and their approximations. Second, when the two criteria are the same %(note that the cost functions continue to be different) we present a ``black box'' parametric search technique. This black box takes in as input an (approximation) algorithm for the unicriterion situation and generates an approximation algorithm for the bicriteria case with only a constant factor loss in the performance guarantee. Third, when the two criteria are the diameter and the total edge costs we use a cluster-based approach to devise a approximation algorithms --- the solutions output violate both the criteria by a logarithmic factor. Finally, for the class of treewidth-bounded graphs, we provide pseudopolynomial-time algorithms for a number of bicriteria problems using dynamic programming. We show how these pseudopolynomial-time algorithms can be converted to fully polynomial-time approximation schemes using a scaling technique.

Connected through hyperedge HE-1 (induced by source paper "tight approximation for variants of directed steiner tree via state tree decomposition and linear programming rounding"):
  with members:
    - "a quasi polynomial algorithm for submodular tree orienteering in directed graphs"
    - "online weighted degree bounded steiner networks via novel online mixed packing covering"
    - "online buy at bulk network design"
    - "approximating directed steiner problems via tree embedding"
    - "directed steiner tree and the lasserre hierarchy"

Connected through hyperedge HE-2 (induced by source paper "online degree bounded steiner network design"):
  with members:
    - "adcell ad allocation in cellular networks"
    - "online stochastic matching beating 1 1 e"

Connected through hyperedge HE-3 (induced by source paper "online weighted degree bounded steiner networks via novel online mixed packing covering"):
  with members:
    - "online buy at bulk network design"

Connected through hyperedge HE-4 (induced by source paper "tight network topology dependent bounds on rounds of communication"):
  with members:
    - "tribes is hard in the message passing model"
    - "distributed computation of large scale graph problems"
    - "when distributed computation is communication expensive"
    - "tight bounds for distributed functional monitoring"
    - "distributed verification and hardness of distributed approximation"

Connected through hyperedge HE-5 (induced by source paper "bicriteria data compression"):
  with members:
    - "on optimally partitioning a text to improve its compression"

Connected through hyperedge HE-6 (induced by source paper "optimization with more than one budget"):
  with members:
    - "dependent randomized rounding for matroid polytopes and applications"

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.CC(Computational Complexity)