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: "language edit distance maximum likelihood parsing of stochastic grammars faster algorithms connection to fundamental graph problems"
  Abstract: Given a context free language $L(G)$ over alphabet $\Sigma$ and a string $s \in \Sigma^*$, the language edit distance (Lan-ED) problem seeks the minimum number of edits (insertions, deletions and substitutions) required to convert $s$ into a valid member of $L(G)$. The well-known dynamic programming algorithm solves this problem in $O(n^3)$ time (ignoring grammar size) where $n$ is the string length [Aho, Peterson 1972, Myers 1985]. Despite its vast number of applications, there is no algorithm known till date that computes or approximates Lan-ED in true sub-cubic time. #R##N#In this paper we give the first such algorithm that computes Lan-ED almost optimally. For any arbitrary $\epsilon > 0$, our algorithm runs in $\tilde{O}(\frac{n^{\omega}}{poly(\epsilon)})$ time and returns an estimate within a multiplicative approximation factor of $(1+\epsilon)$, where $\omega$ is the exponent of ordinary matrix multiplication of $n$ dimensional square matrices. It also computes the edit script. Further, for all substrings of $s$, we can estimate their Lan-ED within $(1\pm \epsilon)$ factor in $\tilde{O}(\frac{n^{\omega}}{poly(\epsilon)})$ time with high probability. We also design the very first sub-cubic ($\tilde{O}(n^\omega)$) algorithm to handle arbitrary stochastic context free grammar (SCFG) parsing. SCFGs lie at the foundation of statistical natural language processing, they generalize hidden Markov models, and have found widespread applications. #R##N#To complement our upper bound result, we show that exact computation of SCFG parsing, or Lan-ED with insertion as only edit operation in true sub-cubic time will imply a truly sub-cubic algorithm for all-pairs shortest paths, and hence to a large range of problems in graphs and matrices. Known lower bound results on parsing implies no improvement over our time bound of $O(n^\omega)$ is possible for any nontrivial multiplicative approximation.

Connected through hyperedge HE-1 (induced by source paper "streaming with oracle new streaming algorithms for edit distance and lcs"):
  with members:
    - "approximating lcs in linear time beating the sqrt n barrier"
    - "dynamic time warping in strongly subquadratic time algorithms for the low distance regime and approximate evaluation"
    - "sublinear algorithms for gap edit distance"
    - "reducing approximate longest common subsequence to approximate edit distance"
    - "constant factor approximation of near linear edit distance in near linear time"
    - "constant factor approximations to edit distance on far input pairs in nearly linear time"
    - "approximating edit distance within constant factor in truly sub quadratic time"
    - "on estimating edit distance alignment dimension reduction and embeddings"

Connected through hyperedge HE-2 (induced by source paper "on the fine grained complexity of parity problems"):
  with members:
    - "subcubic equivalences between graph centrality measures and complementary problems"
    - "approximating subset sum is equivalent to min plus convolution"
    - "on problems equivalent to min convolution"
    - "a subquadratic algorithm for 3xor"
    - "fine grained reductions from approximate counting to decision"
    - "fine grained i o complexity via reductions new lower bounds faster algorithms and a time hierarchy"
    - "on the fine grained complexity of one dimensional dynamic programming"
    - "tight hardness results for maximum weight rectangles"

Connected through hyperedge HE-3 (induced by source paper "more consequences of falsifying seth and the orthogonal vectors conjecture"):
  with members:
    - "on the fine grained complexity of empirical risk minimization kernel methods and neural networks"
    - "conditional lower bounds for all pairs max flow"
    - "on the fine grained complexity of one dimensional dynamic programming"
    - "distributed pcp theorems for hardness of approximation in p"
    - "tree edit distance cannot be computed in strongly subcubic time unless apsp can"
    - "fine grained complexity of analyzing compressed data quantifying improvements over decompress and solve"
    - "improving viterbi is hard better runtimes imply faster clique algorithms"
    - "on the hardness of partially dynamic graph problems and connections to diameter"

Connected through hyperedge HE-4 (induced by source paper "truly sub cubic algorithms for language edit distance and rna folding via fast bounded difference min plus product"):
  with members:
    - "clustered integer 3sum via additive combinatorics"
    - "hardness of rna folding problem with four symbols"
    - "if the current clique algorithms are optimal so is valiant s parser"
    - "powers of tensors and fast matrix multiplication"
    - "an error correcting parser for context free grammars that takes less than cubic time"
    - "faster all pairs shortest paths via circuit complexity"
    - "streaming algorithms for recognizing nearly well parenthesized expressions"
    - "faster algorithms for rectangular matrix multiplication"

Connected through hyperedge HE-5 (induced by source paper "improved bounds for testing dyck languages"):
  with members:
    - "truly sub cubic algorithms for language edit distance and rna folding via fast bounded difference min plus product"
    - "streaming property testing of visibly pushdown languages"
    - "testing closeness of discrete distributions"
    - "recognizing well parenthesized expressions in the streaming model"

Connected through hyperedge HE-6 (induced by source paper "if the current clique algorithms are optimal so is valiant s parser"):
  with members:
    - "an improved combinatorial algorithm for boolean matrix multiplication"
    - "clustered integer 3sum via additive combinatorics"
    - "time and space efficient algorithms for rna folding with the four russians technique"
    - "quadratic conditional lower bounds for string problems and dynamic time warping"
    - "quadratic time hardness of lcs and other sequence similarity measures"
    - "powers of tensors and fast matrix multiplication"
    - "edit distance cannot be computed in strongly subquadratic time unless seth is false"
    - "an error correcting parser for context free grammars that takes less than cubic time"

Connected through hyperedge HE-7 (induced by source paper "hardness of rna folding problem with four symbols"):
  with members:
    - "truly sub cubic algorithms for language edit distance and rna folding via fast bounded difference min plus product"
    - "clustered integer 3sum via additive combinatorics"
    - "time and space efficient algorithms for rna folding with the four russians technique"
    - "if the current clique algorithms are optimal so is valiant s parser"
    - "quadratic conditional lower bounds for string problems and dynamic time warping"
    - "edit distance cannot be computed in strongly subquadratic time unless seth is false"
    - "on hardness of jumbled indexing"
    - "faster all pairs shortest paths via circuit complexity"

Connected through hyperedge HE-8 (induced by source paper "threesomes degenerates and love triangles"):
  with members:
    - "near optimal linear decision trees for k sum and related problems"
    - "connectivity oracles for graphs subject to vertex failures"
    - "subquadratic algorithms for algebraic generalizations of 3sum"
    - "unifying and strengthening hardness for dynamic problems via the online matrix vector multiplication conjecture"
    - "improved bounds for 3sum k sum and linear degeneracy"
    - "clustered integer 3sum via additive combinatorics"
    - "quadratic conditional lower bounds for string problems and dynamic time warping"
    - "why walking the dog takes time frechet distance has no strongly subquadratic algorithms unless seth fails"

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)