human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "deterministic combinatorial replacement paths and distance sensitivity oracles"):
  Abstract: In this work we derandomize two central results in graph algorithms, replacement paths and distance sensitivity oracles (DSOs) matching in both cases the running time of the randomized algorithms. #R##N#For the replacement paths problem, let G = (V,E) be a directed unweighted graph with n vertices and m edges and let P be a shortest path from s to t in G. The {\sl replacement paths} problem is to find for every edge e \in P the shortest path from s to t avoiding e. Roditty and Zwick [ICALP 2005] obtained a randomized algorithm with running time of ~O(m \sqrt{n}). Here we provide the first deterministic algorithm for this problem, with the same ~O(m \sqrt{n}) time. #R##N#For the problem of distance sensitivity oracles, let G = (V,E) be a directed graph with real-edge weights. An f-Sensitivity Distance Oracle (f-DSO) gets as input the graph G=(V,E) and a parameter f, preprocesses it into a data-structure, such that given a query (s,t,F) with s,t \in V and F \subseteq E \cup V, |F| \le f being a set of at most f edges or vertices (failures), the query algorithm efficiently computes the distance from s to t in the graph G \setminus F ({\sl i.e.}, the distance from s to t in the graph G after removing from it the failing edges and vertices F). For weighted graphs with real edge weights, Weimann and Yuster [FOCS 2010] presented a combinatorial randomized f-DSO with ~O(mn^{4-\alpha}) preprocessing time and subquadratic ~O(n^{2-2(1-\alpha)/f}) query time for every value of 0 < \alpha < 1. We derandomize this result and present a combinatorial deterministic f-DSO with the same asymptotic preprocessing and query time.

Includes members:
  Member "a deterministic distributed algorithm for exact weighted all pairs shortest paths in tilde o n 3 2 rounds":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "fast approximate shortest paths in the congested clique")
  Member "dynamic matching reducing integral algorithms to approximately maximal fractional algorithms":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "dynamic graph algorithms with batch updates in the massively parallel computation model")
  Member "generating families of practical fast matrix multiplication algorithms":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "strassen s 2x2 matrix multiplication algorithm a conceptual perspective")
  Member "improved algorithms for decremental single source reachability on directed graphs":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "new algorithms and hardness for incremental single source shortest paths in directed graphs")
  Member "a framework for practical parallel fast matrix multiplication":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "engineering boolean matrix multiplication for multiple accelerator shared memory architectures")
  Member "decremental single source shortest paths on undirected graphs in near linear total update time":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "new algorithms and hardness for incremental single source shortest paths in directed graphs")
  Member "sublinear time decremental algorithms for single source reachability and shortest paths on directed graphs":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "approximate distance oracles subject to multiple vertex failures")
  Member "replacement paths via row minima of concise matrices":
    also connected through other hyperedges:
      (none)

Question: Please tell me which class the source paper 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)