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: "using optimization to obtain a width independent parallel simpler and faster positive sdp solver"
  Abstract: We study the design of polylogarithmic depth algorithms for approximately solving packing and covering semidefinite programs (or positive SDPs for short). This is a natural SDP generalization of the well-studied positive LP problem. #R##N#Although positive LPs can be solved in polylogarithmic depth while using only $\tilde{O}(\log^{2} n/\varepsilon^2)$ parallelizable iterations, the best known positive SDP solvers due to Jain and Yao require $O(\log^{14} n /\varepsilon^{13})$ parallelizable iterations. Several alternative solvers have been proposed to reduce the exponents in the number of iterations. However, the correctness of the convergence analyses in these works has been called into question, as they both rely on algebraic monotonicity properties that do not generalize to matrix algebra. #R##N#In this paper, we propose a very simple algorithm based on the optimization framework proposed for LP solvers. Our algorithm only needs $\tilde{O}(\log^2 n / \varepsilon^2)$ iterations, matching that of the best LP solver. To surmount the obstacles encountered by previous approaches, our analysis requires a new matrix inequality that extends Lieb-Thirring's inequality, and a sign-consistent, randomized variant of the gradient truncation technique proposed in.

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"
    - "a faster cutting plane method and its implications for combinatorial and convex optimization"

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 "improved convergence for ell_ infty and ell_1 regression via iteratively reweighted least squares"):
  with members:
    - "irls and slime mold equivalence and convergence"
    - "on a natural dynamics for linear programming"
    - "using optimization to break the epsilon barrier a faster and simpler width independent algorithm for solving positive linear programs in parallel"
    - "physarum can compute shortest paths"
    - "runtime guarantees for regression problems"
    - "electrical flows laplacian systems and faster approximation of maximum flow in undirected graphs"
    - "sequential and parallel algorithms for mixed packing and covering"

Connected through hyperedge HE-4 (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"
    - "spectral sparsification and regret minimization beyond matrix multiplicative updates"
    - "a parallel approximation algorithm for mixed packing and covering semidefinite programs"
    - "a parallel approximation algorithm for positive semidefinite programming"
    - "twice ramanujan sparsifiers"
    - "sequential and parallel algorithms for mixed packing and covering"

Connected through hyperedge HE-5 (induced by source paper "an sdp based algorithm for linear sized spectral sparsification"):
  with members:
    - "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"
    - "a matrix hyperbolic cosine algorithm and applications"

Connected through hyperedge HE-6 (induced by source paper "much faster algorithms for matrix scaling"):
  with members:
    - "approximate gaussian elimination for laplacians fast sparse and simple"
    - "sparsified cholesky and multigrid solvers for connection laplacians"
    - "linear coupling an ultimate unification of gradient and mirror descent"
    - "using optimization to break the epsilon barrier a faster and simpler width independent algorithm for solving positive linear programs in parallel"
    - "an efficient parallel solver for sdd linear systems"
    - "a simple combinatorial algorithm for solving sdd systems in nearly linear time"
    - "nearly linear time algorithms for graph partitioning graph sparsification and solving linear systems"

Connected through hyperedge HE-7 (induced by source paper "a faster cutting plane method and its implications for combinatorial and convex optimization"):
  with members:
    - "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"
    - "iterative row sampling"

Connected through hyperedge HE-8 (induced by source paper "faster parallel solver for positive linear programs via dynamically bucketed selective coordinate descent"):
  with members:
    - "unified acceleration method for packing and covering problems via diameter reduction"
    - "linear coupling an ultimate unification of gradient and mirror descent"
    - "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"
    - "efficient accelerated coordinate descent methods and faster algorithms for solving linear systems"
    - "parallel coordinate descent for l1 regularized loss minimization"
    - "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.DS(Data Structures and Algorithms)