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: "scheduling with outliers"
  Abstract: In classical scheduling problems, we are given jobs and machines, and have to schedule all the jobs to minimize some objective function. What if each job has a specified profit, and we are no longer required to process all jobs? Instead, we can schedule any subset of jobs whose total profit is at least a (hard) target profit requirement, while still trying to approximately minimize the objective function.#R##N##R##N#We refer to this class of problems as scheduling with outliers . This model was initiated by Charikar and Khuller (SODA '06) for minimum max-response time in broadcast scheduling. In this paper, we consider three other well-studied scheduling objectives: the generalized assignment problem, average weighted completion time, and average flow time, for which LP-based approximation algorithms are provided. Our main results are:#R##N##R##N##R##N#For the minimum average flow time problem on identical machines, we give an LP-based logarithmic approximation algorithm for the unit profits case, and complement this result by presenting a matching integrality gap.#R##N#For the average weighted completion time problem on unrelated machines, we give a constant-factor approximation. The algorithm is based on randomized rounding of the time-indexed LP relaxation strengthened by knapsack-cover inequalities.#R##N#For the generalized assignment problem with outliers, we outline a simple reduction to GAP without outliers to obtain an algorithm whose makespan is within 3 times the optimum makespan, and whose cost is at most (1 + *** ) times the optimal cost.

Connected through hyperedge HE-1 (induced by source paper "on the partition set cover problem"):
  with members:
    - "few cuts meet many point sets"
    - "on partial covering for geometric set systems"
    - "analytical approach to parallel repetition"

Connected through hyperedge HE-2 (induced by source paper "a primal dual approximation algorithm for min sum single machine scheduling problems"):
  with members:
    - "how unsplittable flow covering helps scheduling with job dependent cost functions"
    - "dual techniques for scheduling on a machine with varying speed"
    - "the geometry of scheduling"
    - "approximability of sparse integer programs"

Connected through hyperedge HE-3 (induced by source paper "rejecting jobs to minimize load and maximum flow time"):
  with members:
    - "online scheduling to minimize the maximum delay factor"

Connected through hyperedge HE-4 (induced by source paper "analyzing the optimal neighborhood algorithms for budgeted and partial connected dominating set problems"):
  with members:
    - "improved approximation algorithms for budgeted node weighted steiner problems"
    - "the power of local information in social networks"
    - "online myopic network covering"

Connected through hyperedge HE-5 (induced by source paper "a new approximation technique for resource allocation problems"):
  with members:
    - "matroidal degree bounded minimum spanning trees"
    - "on generalizations of network design problems with degree bounds"
    - "santa claus schedules jobs on unrelated machines"
    - "approximating scheduling machines with capacity constraints"
    - "on allocating goods to maximize fairness"
    - "adaptive uncertainty resolution in bayesian combinatorial optimization problems"

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)