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: "lopsidependency in the moser tardos framework beyond the lopsided lovasz local lemma"
  Abstract: The Lopsided Lov\'{a}sz Local Lemma (LLLL) is a powerful probabilistic principle which has been used in a variety of combinatorial constructions. While originally a general statement about probability spaces, it has recently been transformed into a variety of polynomial-time algorithms. The resampling algorithm of Moser & Tardos (2010) is the most well-known example of this. A variety of criteria have been shown for the LLLL; the strongest possible criterion was shown by Shearer, and other criteria which are easier to use computationally have been shown by Bissacot et al (2011), Pegden (2014), Kolipaka & Szegedy (2011), and Kolipaka, Szegedy, Xu (2012). #R##N#We show a new criterion for the Moser-Tardos algorithm to converge. This criterion is stronger than the LLLL criterion; this is possible because it does not apply in the same generality as the original LLLL; yet, it is strong enough to cover many applications of the LLLL in combinatorics. We show a variety of new bounds and algorithms. A noteworthy application is for $k$-SAT, with bounded occurrences of variables. As shown in Gebauer, Sz\'{a}bo, and Tardos (2011), a $k$-SAT instance in which every variable appears $L \leq \frac{2^{k+1}}{e (k+1)}$ times, is satisfiable. Although this bound is asymptotically tight (in $k$), we improve it to $L \leq \frac{2^{k+1} (1 - 1/k)^k}{k-1} - \frac{2}{k}$ which can be significantly stronger when $k$ is small. #R##N#We introduce a new parallel algorithm for the LLLL. While Moser & Tardos described a simple parallel algorithm for the Lov\'{a}sz Local Lemma, and described a simple sequential algorithm for a form of the Lopsided Lemma, they were not able to combine the two. Our new algorithm applies in nearly all settings in which the sequential algorithm works --- this includes settings covered by our new stronger LLLL criterion.

Connected through hyperedge HE-1 (induced by source paper "deterministic algorithms for the lovasz local lemma simpler more general and more parallel"):
  with members:
    - "algorithms for weighted independent transversals and strong colouring"
    - "deterministic parallel algorithms for bilinear objective functions"
    - "sublogarithmic distributed algorithms for lov asz local lemma and the complexity hierarchy"
    - "deterministic parallel algorithms for fooling polylogarithmic juntas and the lovasz local lemma"
    - "algorithmic and enumerative aspects of the moser tardos distribution"
    - "parallel algorithms and concentration bounds for the lovasz local lemma via witness dags"
    - "new constructive aspects of the lovasz local lemma"
    - "deterministic algorithms for the lovasz local lemma"

Connected through hyperedge HE-2 (induced by source paper "extensions of the algorithmic lovasz local lemma"):
  with members:
    - "beyond the lovasz local lemma point to set correlations and their algorithmic applications"
    - "a local lemma for focused stochastic algorithms"
    - "commutative algorithms approximate the lll distribution"
    - "commutativity in the algorithmic lovasz local lemma"
    - "an algorithmic proof of the lovasz local lemma via resampling oracles"
    - "deterministic algorithms for the lovasz local lemma"
    - "a constructive proof of the general lovasz local lemma"

Connected through hyperedge HE-3 (induced by source paper "algorithms for weighted independent transversals and strong colouring"):
  with members:
    - "algorithmic and enumerative aspects of the moser tardos distribution"
    - "finding perfect matchings in bipartite hypergraphs"
    - "new constructive aspects of the lovasz local lemma"
    - "deterministic algorithms for the lovasz local lemma"
    - "a constructive proof of the general lovasz local lemma"

Connected through hyperedge HE-4 (induced by source paper "a time hierarchy theorem for the local model"):
  with members:
    - "the complexity of distributed edge coloring with small palettes"
    - "lcl problems on grids"
    - "polynomial lower bound for distributed graph coloring in a weak local model"
    - "distributed degree splitting edge coloring and orientations"
    - "survey of distributed decision"
    - "an exponential separation between randomized and deterministic complexity in the local model"
    - "on the complexity of local distributed graph problems"
    - "commutativity in the algorithmic lovasz local lemma"

Connected through hyperedge HE-5 (induced by source paper "commutative algorithms approximate the lll distribution"):
  with members:
    - "a new perspective on stochastic local search and the lovasz local lemma"
    - "sublogarithmic distributed algorithms for lov asz local lemma and the complexity hierarchy"
    - "inapproximability of the independent set polynomial below the shearer threshold"
    - "computing the independence polynomial in shearer s region for the lll"
    - "algorithmic and enumerative aspects of the moser tardos distribution"
    - "commutativity in the algorithmic lovasz local lemma"
    - "parallel algorithms and concentration bounds for the lovasz local lemma via witness dags"
    - "partial resampling to approximate covering integer programs"

Connected through hyperedge HE-6 (induced by source paper "variable version lov asz local lemma beyond shearer s bound"):
  with members:
    - "deterministic parallel algorithms for fooling polylogarithmic juntas and the lovasz local lemma"
    - "uniform sampling through the lov asz local lemma"
    - "computing the independence polynomial in shearer s region for the lll"
    - "approximate counting the lovasz local lemma and inference in graphical models"
    - "focused stochastic local search and the lov asz local lemma"
    - "commutativity in the algorithmic lovasz local lemma"
    - "parallel algorithms and concentration bounds for the lovasz local lemma via witness dags"
    - "an algorithmic proof of the lovasz local lemma via resampling oracles"

Connected through hyperedge HE-7 (induced by source paper "oblivious resampling oracles and parallel algorithms for the lopsided lovasz local lemma"):
  with members:
    - "beyond the lovasz local lemma point to set correlations and their algorithmic applications"
    - "tight analysis of randomized greedy mis"
    - "on derandomizing local distributed algorithms"
    - "algorithmic and enumerative aspects of the moser tardos distribution"
    - "commutativity in the algorithmic lovasz local lemma"
    - "parallel algorithms and concentration bounds for the lovasz local lemma via witness dags"
    - "an improved distributed algorithm for maximal independent set"
    - "greedy sequential maximal independent set and matching are parallel on average"

Connected through hyperedge HE-8 (induced by source paper "the algorithmic lll and the witness tree lemma"):
  with members:
    - "inapproximability of the independent set polynomial below the shearer threshold"
    - "computing the independence polynomial in shearer s region for the lll"
    - "algorithmic and enumerative aspects of the moser tardos distribution"
    - "parallel algorithms and concentration bounds for the lovasz local lemma via witness dags"
    - "partial resampling to approximate covering integer programs"
    - "an algorithmic proof of the lovasz local lemma via resampling oracles"

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)