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: "tight hardness results for maximum weight rectangles"
  Abstract: Given $n$ weighted points (positive or negative) in $d$ dimensions, what is the axis-aligned box which maximizes the total weight of the points it contains? #R##N#The best known algorithm for this problem is based on a reduction to a related problem, the Weighted Depth problem [T. M. Chan, FOCS'13], and runs in time $O(n^d)$. It was conjectured [Barbay et al., CCCG'13] that this runtime is tight up to subpolynomial factors. We answer this conjecture affirmatively by providing a matching conditional lower bound. We also provide conditional lower bounds for the special case when points are arranged in a grid (a well studied problem known as Maximum Subarray problem) as well as for other related problems. #R##N#All our lower bounds are based on assumptions that the best known algorithms for the All-Pairs Shortest Paths problem (APSP) and for the Max-Weight k-Clique problem in edge-weighted graphs are essentially optimal.

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"
    - "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"
    - "on problems as hard as cnf sat"

Connected through hyperedge HE-2 (induced by source paper "truly subcubic min plus product for less structured matrices with applications"):
  with members:
    - "more consequences of falsifying seth and the orthogonal vectors conjecture"
    - "truly sub cubic algorithms for language edit distance and rna folding via fast bounded difference min plus product"
    - "tight hardness for shortest cycles and paths in sparse graphs"
    - "powers of tensors and fast matrix multiplication"
    - "faster all pairs shortest paths via circuit complexity"

Connected through hyperedge HE-3 (induced by source paper "smallest k enclosing rectangle revisited"):
  with members:
    - "on problems equivalent to min convolution"
    - "covering many points with a small area box"
    - "clustered integer 3sum via additive combinatorics"
    - "faster all pairs shortest paths via circuit complexity"

Connected through hyperedge HE-4 (induced by source paper "sublinear subwindow search"):
  with members:
    - "the hunting of the bump on maximizing statistical discrepancy"

Connected through hyperedge HE-5 (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-6 (induced by source paper "fine grained complexity meets ip pspace"):
  with members:
    - "on problems equivalent to min convolution"
    - "hardness of approximate nearest neighbor search"
    - "on the hardness of approximate and exact bichromatic maximum inner product"
    - "tighter connections between formula sat and shaving logs"
    - "conditional lower bounds for all pairs max flow"
    - "conditional lower bounds for space time tradeoffs"
    - "conditional hardness for sensitivity problems"
    - "on the parameterized complexity of approximating dominating set"

Connected through hyperedge HE-7 (induced by source paper "an equivalence class for orthogonal vectors"):
  with members:
    - "on problems equivalent to min convolution"
    - "more consequences of falsifying seth and the orthogonal vectors conjecture"
    - "hardness of approximate nearest neighbor search"
    - "on the hardness of approximate and exact bichromatic maximum inner product"
    - "tight hardness for shortest cycles and paths in sparse graphs"
    - "on the complexity of inner product similarity join"
    - "polynomial representations of threshold functions and algorithmic applications"
    - "strong eth breaks with merlin and arthur short non interactive proofs of batch evaluation"

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)