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: "conditional hardness for sensitivity problems"
  Abstract: In recent years it has become popular to study dynamic problems in a sensitivity setting: Instead of allowing for an arbitrary sequence of updates, the sensitivity model only allows to apply batch updates of small size to the original input data. The sensitivity model is particularly appealing since recent strong conditional lower bounds ruled out fast algorithms for many dynamic problems, such as shortest paths, reachability, or subgraph connectivity. #R##N#In this paper we prove conditional lower bounds for sensitivity problems. For example, we show that under the Boolean Matrix Multiplication (BMM) conjecture combinatorial algorithms cannot compute the (4/3 - {\epsilon})-approximate diameter of an undirected unweighted dense graph with truly subcubic preprocessing time and truly subquadratic update/query time. This result is surprising since in the static setting it is not clear whether a reduction from BMM to diameter is possible. We further show under the BMM conjecture that many problems, such as reachability or approximate shortest paths, cannot be solved faster than by recomputation from scratch even after only one or two edge insertions. We give more lower bounds under the Strong Exponential Time Hypothesis and the All Pairs Shortest Paths Conjecture. Many of our lower bounds also hold for static oracle data structures where no sensitivity is required. Finally, we give the first algorithm for the (1 + {\epsilon})-approximate radius, diameter, and eccentricity problems in directed or undirected unweighted graphs in case of single edges failures. The algorithm has a truly subcubic running time for graphs with a truly subquadratic number of edges; it is tight w.r.t. the conditional lower bounds we obtain.

Connected through hyperedge HE-1 (induced by source paper "sensitive distance and reachability oracles for large batch updates"):
  with members:
    - "dynamic matrix inverse improved algorithms and matching conditional lower bounds"
    - "deterministic combinatorial replacement paths and distance sensitivity oracles"
    - "dynamic approximate shortest paths and beyond subquadratic and worst case update time"
    - "fast deterministic computation of the hermite normal form and determinant of a polynomial matrix"
    - "connectivity oracles for graphs subject to vertex failures"
    - "incremental and fully dynamic subgraph connectivity for emergency planning"
    - "powers of tensors and fast matrix multiplication"
    - "popular conjectures imply strong lower bounds for dynamic problems"

Connected through hyperedge HE-2 (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"
    - "on the parameterized complexity of approximating dominating set"
    - "on the complexity of closest pair via polar pair of point sets"

Connected through hyperedge HE-3 (induced by source paper "algorithms and hardness for diameter in dynamic graphs"):
  with members:
    - "graph pattern detection hardness for all induced patterns and faster non induced cycles"
    - "towards tight approximation bounds for graph diameter and eccentricities"
    - "a note on hardness of diameter approximation"
    - "near linear lower bounds for distributed distance computations even in sparse networks"
    - "unifying and strengthening hardness for dynamic problems via the online matrix vector multiplication conjecture"
    - "decremental single source shortest paths on undirected graphs in near linear total update time"
    - "powers of tensors and fast matrix multiplication"
    - "popular conjectures imply strong lower bounds for dynamic problems"

Connected through hyperedge HE-4 (induced by source paper "nearly optimal separation between partially and fully retroactive data structures"):
  with members:
    - "conditional lower bounds for space time tradeoffs"
    - "popular conjectures as a barrier for dynamic planar graph algorithms"
    - "threesomes degenerates and love triangles"
    - "popular conjectures imply strong lower bounds for dynamic problems"
    - "higher lower bounds from the 3sum conjecture"
    - "fully retroactive approximate range and nearest neighbor searching"
    - "searching in dynamic catalogs on a tree"

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)