human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "symmetric randomized dependent rounding"):
  Abstract: Dependent rounding is a popular technique in designing approximation algorithms. It allows us to randomly round a fractional solution $x$ to an integral vector $X$ such that $E[X] = x$, all $X_i$'s are ("cylindrically") negatively correlated, and the cardinality constraint $\sum_i X_i = \sum_i x_i$ holds with probability one. One can also essentially replace the cardinality constraint by a general linear constraint $\sum_i a_i X_i = \sum_i a_i x_i$ if the $a_i$'s are non-negative. However, in certain problems, the coefficients $a_i$ may have mixed signs; furthermore, some applications require correlation inequalities that are much more general than negative correlation. #R##N#In this paper, we propose a generalized dependent rounding technique, called symmetric randomized dependent rounding, which can round $x$ to an almost-integer vector so that any given linear constraint is satisfied with probability one and such that all the variables are nearly independent. We give two illustrative examples of this technique: a randomized algorithm for the knapsack center problem with new average approximation guarantees and an improved bi-criteria approximation ratio for the knapsack median problem.

Includes members:
  Member "matroid and knapsack center problems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "coreset based strategies for robust center type problems")
  Member "approximating k median via pseudo approximation":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "fair correlation clustering")

Question: Please tell me which class the source paper 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)