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: "lower bounds on near neighbor search via metric expansion"
  Abstract: In this paper we show how the complexity of performing nearest neighbor (NNS) search on a metric space is related to the expansion of the metric space. Given a metric space we look at the graph obtained by connecting every pair of points within a certain distance $r$ . We then look at various notions of expansion in this graph relating them to the cell probe complexity of NNS for randomized and deterministic, exact and approximate algorithms. For example if the graph has node expansion $\Phi$ then we show that any deterministic $t$-probe data structure for $n$ points must use space $S$ where $(St/n)^t > \Phi$. We show similar results for randomized algorithms as well. These relationships can be used to derive most of the known lower bounds in the well known metric spaces such as $l_1$, $l_2$, $l_\infty$ by simply computing their expansion. In the process, we strengthen and generalize our previous results (FOCS 2008). Additionally, we unify the approach in that work and the communication complexity based approach. Our work reduces the problem of proving cell probe lower bounds of near neighbor search to computing the appropriate expansion parameter. In our results, as in all previous results, the dependence on $t$ is weak; that is, the bound drops exponentially in $t$. We show a much stronger (tight) time-space tradeoff for the class of dynamic low contention data structures. These are data structures that supports updates in the data set and that do not look up any single cell too often.

Connected through hyperedge HE-1 (induced by source paper "tight static lower bounds for non adaptive data structures"):
  with members:
    - "static data structure lower bounds imply rigidity"
    - "crossing the logarithmic barrier for dynamic boolean data structure lower bounds"
    - "amortized dynamic cell probe lower bounds from four party communication"
    - "set membership with non adaptive bit probes"
    - "set membership with a few bit probes"
    - "the cell probe complexity of dynamic range counting"
    - "the power of simple tabulation hashing"
    - "linear probing with constant independence"

Connected through hyperedge HE-2 (induced by source paper "on the i o complexity of the k nearest neighbor problem"):
  with members:
    - "approximate nearest neighbor search in high dimensions"
    - "hardness of approximate nearest neighbor search"
    - "optimal hashing based time space trade offs for approximate near neighbors"
    - "neural codes for image retrieval"
    - "efficient distributed locality sensitive hashing"
    - "lower bounds on performance of metric tree indexing schemes for exact similarity search in high dimensions"
    - "dynamic external hashing the limit of buffering"
    - "indexing schemes for similarity search an illustrated paradigm"

Connected through hyperedge HE-3 (induced by source paper "algorithms for similarity search and pseudorandomness"):
  with members:
    - "hardness of approximate nearest neighbor search"
    - "fast locality sensitive hashing for approximate near neighbor search"
    - "fast similarity sketching"
    - "embedjoin efficient edit similarity joins via embeddings"
    - "optimal densification for fast and accurate minwise hashing"
    - "parameter free locality sensitive hashing for spherical range reporting"
    - "scalable and robust set similarity join"
    - "fast cross polytope locality sensitive hashing"

Connected through hyperedge HE-4 (induced by source paper "data structures meet cryptography 3sum with preprocessing"):
  with members:
    - "the strong 3sum indexing conjecture is false"
    - "equivalence of systematic linear data structures and matrix rigidity"
    - "lower bounds for oblivious data structures"
    - "static data structure lower bounds imply rigidity"
    - "how hard is it to find honest witnesses"
    - "conditional lower bounds for space time tradeoffs"
    - "orthogonal vectors indexing"
    - "clustered integer 3sum via additive combinatorics"

Connected through hyperedge HE-5 (induced by source paper "lower bounds for oblivious near neighbor search"):
  with members:
    - "sanns scaling up secure approximate k nearest neighbors search"
    - "hardness of approximate nearest neighbor search"
    - "scalable secure computation of statistical functions with applications to k nearest neighbors"
    - "lower bounds for oblivious data structures"
    - "distributed pcp theorems for hardness of approximation in p"
    - "crossing the logarithmic barrier for dynamic boolean data structure lower bounds"
    - "new unconditional hardness results for dynamic and online problems"
    - "secure k nearest neighbor query over encrypted data in outsourced environments"

Connected through hyperedge HE-6 (induced by source paper "3sum with preprocessing algorithms lower bounds and cryptographic applications"):
  with members:
    - "encoding 3sum"
    - "static data structure lower bounds imply rigidity"
    - "near optimal linear decision trees for k sum and related problems"
    - "conditional lower bounds for space time tradeoffs"
    - "orthogonal vectors indexing"
    - "clustered integer 3sum via additive combinatorics"
    - "threesomes degenerates and love triangles"
    - "on hardness of jumbled indexing"

Connected through hyperedge HE-7 (induced by source paper "equivalence of systematic linear data structures and matrix rigidity"):
  with members:
    - "static data structure lower bounds imply rigidity"
    - "matrix rigidity and the croot lev pach lemma"
    - "crossing the logarithmic barrier for dynamic boolean data structure lower bounds"
    - "probabilistic rank and matrix rigidity"
    - "unifying and strengthening hardness for dynamic problems via the online matrix vector multiplication conjecture"
    - "new unconditional hardness results for dynamic and online problems"
    - "adapt or die polynomial lower bounds for non adaptive dynamic data structures"
    - "min rank conjecture for log depth circuits"

Connected through hyperedge HE-8 (induced by source paper "new amortized cell probe lower bounds for dynamic problems"):
  with members:
    - "amortized dynamic cell probe lower bounds from four party communication"
    - "unifying and strengthening hardness for dynamic problems via the online matrix vector multiplication conjecture"
    - "cell probe lower bounds for dynamic problems via a new communication model"
    - "new unconditional hardness results for dynamic and online problems"
    - "popular conjectures imply strong lower bounds for dynamic problems"
    - "don t rush into a union take time to find your roots"
    - "the cell probe complexity of dynamic range counting"
    - "logarithmic lower bounds in the cell probe model"

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)