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 "online stochastic max weight matching prophet inequality for vertex and edge arrival models"):
  Abstract: We provide prophet inequality algorithms for online weighted matching in general (non-bipartite) graphs, under two well-studied arrival models, namely edge arrival and vertex arrival. The weight of each edge is drawn independently from an a-priori known probability distribution. Under edge arrival, the weight of each edge is revealed upon arrival, and the algorithm decides whether to include it in the matching or not. Under vertex arrival, the weights of all edges from the newly arriving vertex to all previously arrived vertices are revealed, and the algorithm decides which of these edges, if any, to include in the matching. To study these settings, we introduce a novel unified framework of batched prophet inequalities that captures online settings where elements arrive in batches; in particular it captures matching under the two aforementioned arrival models. Our algorithms rely on the construction of suitable online contention resolution scheme (OCRS). We first extend the framework of OCRS to batched-OCRS, we then establish a reduction from batched prophet inequality to batched OCRS, and finally we construct batched OCRSs with selectable ratios of 0.337 and 0.5 for edge and vertex arrival models, respectively. Both results improve the state of the art for the corresponding settings. For the vertex arrival, our result is tight. Interestingly, a pricing-based prophet inequality with comparable competitive ratios is unknown.

Includes members:
  Member "beating greedy for stochastic bipartite matching":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "online graph matching problems with a worst case reassignment budget")
  Member "online stochastic matching with edge arrivals":
    also connected through other hyperedges:
      (none)
  Member "optimal single choice prophet inequalities from samples":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "prophet inequalities with linear correlations and augmentations")
  Member "an optimal monotone contention resolution scheme for bipartite matchings via a polyhedral viewpoint":
    also connected through other hyperedges:
      (none)
  Member "near optimal online algorithms and fast approximation algorithms for resource allocation problems":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "robust online composition routing and nf placement for nfv enabled services")
  Member "prophet inequality for bipartite matching merits of being simple and non adaptive":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "optimal single choice prophet inequalities from samples")
  Member "tight competitive ratios of classic matching algorithms in the fully online model":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "online graph matching problems with a worst case reassignment budget")
  Member "how to match when all vertices arrive online":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "online graph matching problems with a worst case reassignment budget")

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)