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 subquadratic algorithm for 3xor"
  Abstract: Given a set $X$ of $n$ binary words of equal length $w$, the 3XOR problem asks for three elements $a, b, c \in X$ such that $a \oplus b=c$, where $ \oplus$ denotes the bitwise XOR operation. The problem can be easily solved on a word RAM with word length $w$ in time $O(n^2 \log{n})$. Using Han's fast integer sorting algorithm (2002/2004) this can be reduced to $O(n^2 \log{\log{n}})$. With randomization or a sophisticated deterministic dictionary construction, creating a hash table for $X$ with constant lookup time leads to an algorithm with (expected) running time $O(n^2)$. At present, seemingly no faster algorithms are known. We present a surprisingly simple deterministic, quadratic time algorithm for 3XOR. Its core is a version of the Patricia trie for $X$, which makes it possible to traverse the set $a \oplus X$ in ascending order for arbitrary $a\in \{0, 1\}^{w}$ in linear time. #R##N#Furthermore, we describe a randomized algorithm for 3XOR with expected running time $O(n^2\cdot\min\{\log^3{w}/w, (\log\log{n})^2/\log^2 n\})$. The algorithm transfers techniques to our setting that were used by Baran, Demaine, and P\u{a}tra\c{s}cu (2005/2008) for solving the related int3SUM problem (the same problem with integer addition in place of binary XOR) in expected time $o(n^2)$. As suggested by Jafargholi and Viola (2016), linear hash functions are employed. The latter authors also showed that assuming 3XOR needs expected running time $n^{2-o(1)}$ one can prove conditional lower bounds for triangle enumeration just as with 3SUM. We demonstrate that 3XOR can be reduced to other problems as well, treating the examples offline SetDisjointness and offline SetIntersection, which were studied for 3SUM by Kopelowitz, Pettie, and Porat (2016).

Connected through hyperedge HE-1 (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"
    - "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"
    - "on problems as hard as cnf sat"

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)