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: "a ptas for a class of stochastic dynamic programs"
  Abstract: We develop a framework for obtaining polynomial time approximation schemes (PTAS) for a class of stochastic dynamic programs. Using our framework, we obtain the first PTAS for the following stochastic combinatorial optimization problems: \probemax: We are given a set of $n$ items, each item $i\in [n]$ has a value $X_i$ which is an independent random variable with a known (discrete) distribution $\pi_i$. We can {\em probe} a subset $P\subseteq [n]$ of items sequentially. Each time after {probing} an item $i$, we observe its value realization, which follows the distribution $\pi_i$. We can {\em adaptively} probe at most $m$ items and each item can be probed at most once. The reward is the maximum among the $m$ realized values. Our goal is to design an adaptive probing policy such that the expected value of the reward is maximized. To the best of our knowledge, the best known approximation ratio is $1-1/e$, due to Asadpour \etal~\cite{asadpour2015maximizing}. We also obtain PTAS for some generalizations and variants of the problem and some other problems.

Connected through hyperedge HE-1 (induced by source paper "near optimal adaptivity gaps for stochastic multi value probing"):
  with members:
    - "adaptivity gaps for stochastic probing submodular and xos functions"
    - "combinatorial prophet inequalities"
    - "discrete stochastic submodular maximization adaptive vs non adaptive vs offline"
    - "improved approximation algorithms for stochastic matching"
    - "approximation algorithms for stochastic boolean function evaluation and stochastic submodular set cover"
    - "submodular stochastic probing on matroids"
    - "on the adaptivity gap of stochastic orienteering"
    - "a stochastic probing problem with applications"

Connected through hyperedge HE-2 (induced by source paper "algorithms and adaptivity gaps for stochastic k tsp"):
  with members:
    - "an fptas for stochastic unbounded min knapsack problem"
    - "the price of information in combinatorial optimization"
    - "descending price coordinates approximately efficient search"
    - "a stochastic probing problem with applications"
    - "approximation algorithms for correlated knapsacks and non martingale bandits"

Connected through hyperedge HE-3 (induced by source paper "nearly optimal pricing algorithms for production constrained and laminar bayesian selection"):
  with members:
    - "mechanism design for subadditive agents via an ex ante relaxation"
    - "online contention resolution schemes"
    - "a simple and approximately optimal mechanism for an additive buyer"
    - "matroid prophet inequalities"
    - "stochastic combinatorial optimization via poisson approximation"
    - "bayesian combinatorial auctions expanding single buyer mechanisms to many buyers"

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)