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: "orthogonal range searching on the ram revisited"
  Abstract: We present several new results on one of the most extensively studied topics in computational geometry, orthogonal range searching. All our results are in the standard word RAM model for points in rank space: #R##N#** We present two data structures for 2-d orthogonal range emptiness. The first achieves O(n lglg n) space and O(lglg n) query time. This improves the previous results by Alstrup, Brodal, and Rauhe(FOCS'00), with O(n lg^eps n) space and O(lglg n) query time, or with O(nlglg n) space and O(lg^2 lg n) query time. Our second data structure uses O(n) space and answers queries in O(lg^eps n) time. The best previous O(n)-space data structure, due to Nekrich (WADS'07), answers queries in O(lg n/lglg n) time. #R##N#** For 3-d orthogonal range reporting, we obtain space O(n lg^{1+eps} n) and query time O(lglg n + k), for any constant eps>0. This improves previous results by Afshani (ESA'08), Karpinski and Nekrich (COCOON'09), and Chan (SODA'11), with O(n lg^3 n) space and O(lglg n + k) query time, or with O(n lg^{1+eps} n) space and O(lg^2 lg n + k) query time. This implies improved bounds for orthogonal range reporting in all constant dimensions above 3. #R##N#** We give a randomized algorithm for 4-d offline dominance range reporting/emptiness with running time O(n lg n + k). This resolves two open problems from Preparata and Shamos' seminal book: #R##N#**** given n axis-aligned rectangles in the plane, we can report all k enclosure pairs in O(n lg n + k) expected time. The best known result was an O([n lg n + k] lglg n) algorithm from SoCG'95 by Gupta, Janardan, Smid, and Dasgupta. #R##N#**** given n points in 4-d, we can find all maximal points in O(n lg n) expected time. The best previous result was an O(n lg n lglg n) algorithm due to Gabow, Bentley, and Tarjan (STOC'84). This implies record time bounds for the maxima problem in all constant dimensions above 4.

Connected through hyperedge HE-1 (induced by source paper "path query data structures in practice"):
  with members:
    - "aggregated 2d range queries on clustered points"
    - "succinct representations of permutations and functions"
    - "range quantile queries another virtue of wavelet trees"
    - "succinct indexable dictionaries with applications to encoding k ary trees prefix sums and multisets"
    - "range mode and range median queries on lists and trees"

Connected through hyperedge HE-2 (induced by source paper "extending general compact querieable representations to gis applications"):
  with members:
    - "compressed representation of dynamic binary relations with applications"
    - "a succinct data structure for self indexing ternary relations"
    - "aggregated 2d range queries on clustered points"

Connected through hyperedge HE-3 (induced by source paper "quantum inspired classical sublinear time algorithm for solving low rank semidefinite programming via sampling approaches"):
  with members:
    - "a quantum inspired classical algorithm for recommendation systems"
    - "fully dynamic maximal independent set with sublinear update time"
    - "approximate nearest neighbor search in high dimensions"
    - "solving linear programs in the current matrix multiplication time"
    - "quantum inspired low rank stochastic regression with logarithmic dependence on the dimension"
    - "quantum inspired sublinear classical algorithms for solving low rank linear systems"
    - "quantum inspired classical algorithms for principal component analysis and supervised clustering"
    - "fully dynamic approximate maximum matching and minimum vertex cover in o log 3 n worst case update time"

Connected through hyperedge HE-4 (induced by source paper "energy consumption in compact integer vectors a study case"):
  with members:
    - "energy efficient algorithms"
    - "compact binary relation representations with rich functionality"
    - "optimal lower and upper bounds for representing sequences"
    - "on compressing permutations and adaptive sorting"
    - "succinct representations of permutations and functions"
    - "fully functional static and dynamic succinct trees"
    - "succinct indexable dictionaries with applications to encoding k ary trees prefix sums and multisets"
    - "practical entropy compressed rank select dictionary"

Connected through hyperedge HE-5 (induced by source paper "counting small permutation patterns"):
  with members:
    - "faster and simpler algorithms for finding large patterns in permutations"
    - "finding and counting permutations via csps"
    - "improved bounds for testing forbidden order patterns"
    - "finding small patterns in permutations in linear time"
    - "the computational landscape of permutation patterns"
    - "a fast algorithm for permutation pattern matching based on alternating runs"
    - "hereditary properties of permutations are strongly testable"

Connected through hyperedge HE-6 (induced by source paper "sparse regression via range counting"):
  with members:
    - "approximate sparse linear regression"
    - "online sparse linear regression"
    - "variable selection is hard"

Connected through hyperedge HE-7 (induced by source paper "dynamic geometric data structures via shallow cuttings"):
  with members:
    - "dynamic planar voronoi diagrams for general distance functions and their algorithmic applications"
    - "faster fully dynamic minimum spanning forest"
    - "fast hierarchical clustering and other applications of dynamic closest pairs"

Connected through hyperedge HE-8 (induced by source paper "multitask and transfer learning for autotuning exascale applications"):
  with members:
    - "a survey on multi task learning"
    - "hyperband a novel bandit based approach to hyperparameter optimization"

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.CG(Computational Geometry)