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: "blind unwrapping of modulo reduced gaussian vectors recovering msbs from lsbs"
  Abstract: We consider the problem of recovering $n$ i.i.d samples from a zero mean multivariate Gaussian distribution with an unknown covariance matrix, from their modulo wrapped measurements, i.e., measurement where each coordinate is reduced modulo $\Delta$, for some $\Delta>0$. For this setup, which is motivated by quantization and analog-to-digital conversion, we develop a low-complexity iterative decoding algorithm. We show that if a benchmark informed decoder that knows the covariance matrix can recover each sample with small error probability, and $n$ is large enough, the performance of the proposed blind recovery algorithm closely follows that of the informed one. We complement the analysis with numeric results that show that the algorithm performs well even in non-asymptotic conditions.

Connected through hyperedge HE-1 (induced by source paper "on unlimited sampling and reconstruction"):
  with members:
    - "above the nyquist rate modulo folding does not hurt"
    - "a modulo based architecture for analog to digital conversion"
    - "on unlimited sampling"
    - "integer forcing linear receivers"

Connected through hyperedge HE-2 (induced by source paper "above the nyquist rate modulo folding does not hurt"):
  with members:
    - "a modulo based architecture for analog to digital conversion"
    - "on unlimited sampling"
    - "integer forcing source coding"

Connected through hyperedge HE-3 (induced by source paper "achievability performance bounds for integer forcing source coding"):
  with members:
    - "outage behavior of integer forcing with random unitary pre processing"
    - "successive integer forcing and its sum rate optimality"
    - "precoded integer forcing universally achieves the mimo capacity to within a constant gap"
    - "integer forcing source coding"
    - "the approximate sum capacity of the symmetric gaussian k user interference channel"
    - "a simple proof for the existence of good pairs of nested lattices"

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)