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: "a parallel approximation algorithm for positive semidefinite programming"
  Abstract: Positive semidefinite programs are an important subclass of semidefinite programs in which all matrices involved in the specification of the problem are positive semidefinite and all scalars involved are non-negative. We present a parallel algorithm, which given an instance of a positive semidefinite program of size N and an approximation factor eps > 0, runs in (parallel) time poly(1/eps) \cdot polylog(N), using poly(N) processors, and outputs a value which is within multiplicative factor of (1 + eps) to the optimal. Our result generalizes analogous result of Luby and Nisan [1993] for positive linear programs and our algorithm is inspired by their algorithm.

Connected through hyperedge HE-1 (induced by source paper "positive semidefinite programming mixed parallel and width independent"):
  with members:
    - "a rank 1 sketch for matrix multiplicative weights"
    - "non convex matrix completion against a semi random adversary"
    - "high dimensional robust mean estimation in nearly linear time"
    - "efficient structured matrix recovery and nearly linear time algorithms for solving inverse symmetric m matrices"
    - "an sdp based algorithm for linear sized spectral sparsification"
    - "follow the compressed leader faster online learning of eigenvectors and faster mmwu"
    - "hardness results for structured linear systems"
    - "using optimization to obtain a width independent parallel simpler and faster positive sdp solver"

Connected through hyperedge HE-2 (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-3 (induced by source paper "finding sparse solutions for packing and covering semidefinite programs"):
  with members:
    - "an sdp based algorithm for linear sized spectral sparsification"
    - "sparse sums of positive semidefinite matrices"
    - "using optimization to obtain a width independent parallel simpler and faster positive sdp solver"
    - "spectral sparsification and regret minimization beyond matrix multiplicative updates"
    - "a parallel approximation algorithm for mixed packing and covering semidefinite programs"
    - "twice ramanujan sparsifiers"
    - "sequential and parallel algorithms for mixed packing and covering"

Connected through hyperedge HE-4 (induced by source paper "an sdp based algorithm for linear sized spectral sparsification"):
  with members:
    - "using optimization to obtain a width independent parallel simpler and faster positive sdp solver"
    - "sparsified cholesky and multigrid solvers for connection laplacians"
    - "spectral sparsification and regret minimization beyond matrix multiplicative updates"
    - "constructing linear sized spectral sparsification in almost linear time"
    - "uniform sampling for matrix approximation"
    - "an efficient parallel solver for sdd linear systems"
    - "iterative row sampling"
    - "osnap faster numerical linear algebra algorithms via sparser subspace embeddings"

Connected through hyperedge HE-5 (induced by source paper "sparse sums of positive semidefinite matrices"):
  with members:
    - "a matrix hyperbolic cosine algorithm and applications"
    - "faster spectral sparsification and numerical algorithms for sdd matrices"
    - "near optimal column based matrix reconstruction"
    - "graph sparsification by edge connectivity and random spanning trees"
    - "towards an sdp based approach to spectral methods a nearly linear time algorithm for graph partitioning and decomposition"
    - "a linear time algorithm for sparsification of unweighted graphs"
    - "graph sparsification via refinement sampling"
    - "approaching optimality for solving sdd systems"

Connected through hyperedge HE-6 (induced by source paper "a faster cutting plane method and its implications for combinatorial and convex optimization"):
  with members:
    - "using optimization to obtain a width independent parallel simpler and faster positive sdp solver"
    - "efficient inverse maintenance and faster algorithms for linear programming"
    - "powers of tensors and fast matrix multiplication"
    - "bayesian truthful mechanisms for job scheduling from bi criterion approximation algorithms"
    - "uniform sampling for matrix approximation"
    - "reducing revenue to welfare maximization approximation algorithms and other generalizations"
    - "path finding ii an o m sqrt n algorithm for the minimum cost flow problem"
    - "optimal multi dimensional mechanism design reducing revenue to welfare maximization"

Connected through hyperedge HE-7 (induced by source paper "using optimization to obtain a width independent parallel simpler and faster positive sdp solver"):
  with members:
    - "spectral sparsification and regret minimization beyond matrix multiplicative updates"
    - "a nearly linear time ptas for explicit fractional packing and covering linear programs"
    - "using optimization to break the epsilon barrier a faster and simpler width independent algorithm for solving positive linear programs in parallel"
    - "nearly linear time approximation schemes for mixed packing covering and facility location linear programs"
    - "a parallel approximation algorithm for mixed packing and covering semidefinite programs"
    - "approximating the exponential the lanczos method and an tilde o m time spectral algorithm for balanced separator"
    - "two message quantum interactive proofs are in pspace"
    - "sequential and parallel algorithms for mixed packing and covering"

Connected through hyperedge HE-8 (induced by source paper "a parallel approximation algorithm for mixed packing and covering semidefinite programs"):
  with members:
    - "faster and simpler width independent parallel algorithms for positive semidefinite programming"
    - "two message quantum interactive proofs are in pspace"
    - "sequential and parallel algorithms for mixed packing and covering"

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)