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: "on the restricted isometry property of centered self khatri rao products"
  Abstract: In this work we establish the Restricted Isometry Property (RIP) of the centered column-wise self Khatri-Rao (KR) products of $n\times N$ matrix with iid columns drawn either uniformly from a sphere or with iid sub-Gaussian entries. The self KR product is an $n^2\times N$-matrix which contains as columns the vectorized (self) outer products of the columns of the original $n\times N$-matrix. Based on a result of Adamczak et al. we show that such a centered self KR product with independent heavy tailed columns has small RIP constants of order $s$ with probability at least $1-C\exp(-cn)$ provided that $s\lesssim n^2/\log^2(eN/n^2)$. Our result is applicable in various works on covariance matching like in activity detection and MIMO gain-estimation.

Connected through hyperedge HE-1 (induced by source paper "grant free massive random access with a massive mimo receiver"):
  with members:
    - "phase transition analysis for covariance based massive random access with massive mimo"
    - "non bayesian activity detection large scale fading coefficient estimation and unsourced random access with a massive mimo receiver"
    - "polar coding and random spreading for unsourced multiple access"
    - "an enhanced decoding algorithm for coded compressed sensing"
    - "improved scaling law for activity detection in massive mimo systems"
    - "on the fly large scale channel gain estimation for massive antenna array base stations"
    - "on the restricted isometry of the columnwise khatri rao product"
    - "sparse activity detection for massive connectivity"

Connected through hyperedge HE-2 (induced by source paper "binary component decomposition part i the positive semidefinite case"):
  with members:
    - "binary component decomposition part ii the asymmetric case"
    - "improved scaling law for activity detection in massive mimo systems"
    - "sparse activity detection for massive connectivity"
    - "massive connectivity with massive mimo part i device activity detection and channel estimation"
    - "structured low rank matrix factorization global optimality algorithms and applications"
    - "hierarchical compound poisson factorization"
    - "a faster cutting plane method and its implications for combinatorial and convex optimization"
    - "convex relaxations of structured matrix factorizations"

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.IT(Information Theory)