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 of earth mover distance"
  Abstract: The Earth Mover Distance (EMD) between two sets of points $A, B \subseteq \mathbb{R}^d$ with $|A| = |B|$ is the minimum total Euclidean distance of any perfect matching between $A$ and $B$. One of its generalizations is asymmetric EMD, which is the minimum total Euclidean distance of any matching of size $|A|$ between sets of points $A,B \subseteq \mathbb{R}^d$ with $|A| \leq |B|$. The problems of computing EMD and asymmetric EMD are well-studied and have many applications in computer science, some of which also ask for the EMD-optimal matching itself. Unfortunately, all known algorithms require at least quadratic time to compute EMD exactly. Approximation algorithms with nearly linear time complexity in $n$ are known (even for finding approximately optimal matchings), but suffer from exponential dependence on the dimension. #R##N#In this paper we show that significant improvements in exact and approximate algorithms for EMD would contradict conjectures in fine-grained complexity. In particular, we prove the following results: #R##N#(1) Under the Orthogonal Vectors Conjecture, there is some $c>0$ such that EMD in $\Omega(c^{\log^* n})$ dimensions cannot be computed in truly subquadratic time. #R##N#(2) Under the Hitting Set Conjecture, for every $\delta>0$, no truly subquadratic time algorithm can find a $(1 + 1/n^\delta)$-approximate EMD matching in $\omega(\log n)$ dimensions. #R##N#(3) Under the Hitting Set Conjecture, for every $\eta = 1/\omega(\log n)$, no truly subquadratic time algorithm can find a $(1 + \eta)$-approximate asymmetric EMD matching in $\omega(\log n)$ dimensions.

Connected through hyperedge HE-1 (induced by source paper "scheduling lower bounds via and subset sum"):
  with members:
    - "polyline simplification has cubic complexity"
    - "a simple near linear pseudopolynomial time randomized algorithm for subset sum"
    - "fast modular subset sum using linear sketching"
    - "algorithms and hardness for diameter in dynamic graphs"
    - "seth based lower bounds for subset sum and bicriteria path"
    - "fine grained i o complexity via reductions new lower bounds faster algorithms and a time hierarchy"
    - "on problems as hard as cnf sat"
    - "a near linear pseudopolynomial time algorithm for subset sum"

Connected through hyperedge HE-2 (induced by source paper "a data dependent algorithm for querying earth mover s distance with low doubling dimension"):
  with members:
    - "near linear time approximation algorithms for optimal transport via sinkhorn iteration"
    - "optimal transport for domain adaptation"
    - "a survey on truth discovery"
    - "on constant factor approximation for earth mover distance over doubling metrics"
    - "fast construction of nets in low dimensional metrics and their applications"

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.CC(Computational Complexity)