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: "the submodular secretary problem goes linear"
  Abstract: During the last decade, the matroid secretary problem (MSP) became one of the most prominent classes of online selection problems. Partially linked to its numerous applications in mechanism design, substantial interest arose also in the study of nonlinear versions of MSP, with a focus on the submodular matroid secretary problem (SMSP). So far, O(1)-competitive algorithms have been obtained for SMSP over some basic matroid classes. This created some hope that, analogously to the matroid secretary conjecture, one may even obtain O(1)-competitive algorithms for SMSP over any matroid. However, up to now, most questions related to SMSP remained open, including whether SMSP may be substantially more difficult than MSP; and more generally, to what extend MSP and SMSP are related. #R##N#Our goal is to address these points by presenting general black-box reductions from SMSP to MSP. In particular, we show that any O(1)-competitive algorithm for MSP, even restricted to a particular matroid class, can be transformed in a black-box way to an O(1)-competitive algorithm for SMSP over the same matroid class. This implies that the matroid secretary conjecture is equivalent to the same conjecture for SMSP. Hence, in this sense SMSP is not harder than MSP. Also, to find O(1)-competitive algorithms for SMSP over a particular matroid class, it suffices to consider MSP over the same matroid class. Using our reductions we obtain many first and improved O(1)-competitive algorithms for SMSP over various matroid classes by leveraging known algorithms for MSP. Moreover, our reductions imply an O(loglog(rank))-competitive algorithm for SMSP, thus, matching the currently best asymptotic algorithm for MSP, and substantially improving on the previously best O(log(rank))-competitive algorithm for SMSP.

Connected through hyperedge HE-1 (induced by source paper "submodular matroid secretary problem with shortlists"):
  with members:
    - "quasi polynomial algorithms for submodular tree orienteering and other directed network design problems"
    - "submodular streaming in all its glory tight approximation minimum memory and low adaptive complexity"
    - "submodular secretary problem with shortlists"
    - "do less get more streaming submodular maximization with subsampling"
    - "beyond 1 2 approximation for submodular maximization on massive data streams"
    - "a logarithmic integrality gap bound for directed steiner tree in quasi bipartite graphs"
    - "submodular secretary problems cardinality matching and linear constraints"
    - "streaming algorithms for submodular function maximization"

Connected through hyperedge HE-2 (induced by source paper "budget feasible mechanism design for non monotone submodular objectives offline and online"):
  with members:
    - "a nearly linear time algorithm for submodular maximization with a knapsack constraint"
    - "on budget feasible mechanism design for symmetric submodular objectives"
    - "simple and efficient budget feasible mechanisms for monotone submodular valuations"
    - "greed is good near optimal submodular maximization via greedy optimization"
    - "budget feasible mechanisms on matroids"
    - "adaptivity gaps for stochastic probing submodular and xos functions"
    - "coverage matching and beyond new results on budgeted mechanism design"
    - "submodular secretary problems cardinality matching and linear constraints"

Connected through hyperedge HE-3 (induced by source paper "competitive online optimization under inventory constraints"):
  with members:
    - "balancing cost and dissatisfaction in online ev charging under real time pricing"
    - "nested convex bodies are chaseable"
    - "beyond matroids secretary problem and prophet inequality with general constraints"
    - "online offering strategies for storage assisted renewable power producer in hour ahead market"
    - "online convex optimization using predictions"
    - "a tale of two metrics simultaneous bounds on competitiveness and regret"
    - "peak aware online economic dispatching for microgrids"
    - "online energy generation scheduling for microgrids with intermittent energy sources and co generation"

Connected through hyperedge HE-4 (induced by source paper "an improved algorithm for the submodular secretary problem with a cardinality constraint"):
  with members:
    - "combinatorial prophet inequalities"
    - "constrained submodular maximization via a non symmetric technique"
    - "submodular secretary problems cardinality matching and linear constraints"
    - "building a good team secretary problems and the supermodular degree"
    - "the simulated greedy algorithm for several submodular matroid secretary problems"
    - "constrained non monotone submodular maximization offline and secretary algorithms"

Connected through hyperedge HE-5 (induced by source paper "strong algorithms for the ordinal matroid secretary problem"):
  with members:
    - "combinatorial secretary problems with ordinal information"
    - "combinatorial prophet inequalities"
    - "beyond matroids secretary problem and prophet inequality with general constraints"
    - "secretary problems with non uniform arrival order"
    - "o log log rank competitive ratio for the matroid secretary problem"
    - "a simple o log log mathrm rank competitive algorithm for the matroid secretary problem"
    - "prophet inequalities with limited information"
    - "polymatroid prophet inequalities"

Connected through hyperedge HE-6 (induced by source paper "submodular secretary problem with shortlists"):
  with members:
    - "online submodular maximization beating 1 2 made simple"
    - "the submodular secretary problem under a cardinality constraint and with limited resources"
    - "online submodular welfare maximization greedy beats 1 2 in random order"
    - "submodular secretary problems cardinality matching and linear constraints"
    - "lazier than lazy greedy"
    - "submodular maximization meets streaming matchings matroids and more"
    - "online submodular welfare maximization greedy is optimal"
    - "online stochastic packing applied to display ad allocation"

Connected through hyperedge HE-7 (induced by source paper "packing returning secretaries"):
  with members:
    - "combinatorial secretary problems with ordinal information"
    - "beyond matroids secretary problem and prophet inequality with general constraints"
    - "submodular secretary problems cardinality matching and linear constraints"
    - "the temp secretary problem"
    - "o log log rank competitive ratio for the matroid secretary problem"
    - "online independent set beyond the worst case secretaries prophets and periods"
    - "algorithms for secretary problems on graphs and hypergraphs"

Connected through hyperedge HE-8 (induced by source paper "maximizing profit with convex costs in the random order model"):
  with members:
    - "near optimal online algorithms and fast approximation algorithms for resource allocation problems"
    - "fast algorithms for online stochastic convex programming"
    - "how the experts algorithm can help solve lps online"
    - "o log log rank competitive ratio for the matroid secretary problem"
    - "a dynamic near optimal algorithm for online linear programming"

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)