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 solving a generalized chinese remainder theorem in the presence of remainder errors"
  Abstract: In estimating frequencies given that the signal waveforms are undersampled multiple times, Xia et. al. proposed to use a generalized version of Chinese remainder Theorem (CRT), where the moduli are $M_1, M_2, \cdots, M_k$ which are not necessarily pairwise coprime. If the errors of the corrupted remainders are within $\tau=\sds \max_{1\le i\le k} \min_{\stackrel{1\le j\le k}{j\neq i}} \frac{\gcd(M_i,M_j)}4$, their schemes can be used to construct an approximation of the solution to the generalized CRT with an error smaller than $\tau$. Accurately finding the quotients is a critical ingredient in their approach. In this paper, we shall start with a faithful historical account of the generalized CRT. We then present two treatments of the problem of solving generalized CRT with erroneous remainders. The first treatment follows the route of Wang and Xia to find the quotients, but with a simplified process. The second treatment considers a simplified model of generalized CRT and takes a different approach by working on the corrupted remainders directly. This approach also reveals some useful information about the remainders by inspecting extreme values of the erroneous remainders modulo $4\tau$. Both of our treatments produce efficient algorithms with essentially optimal performance. Finally, this paper constructs a counterexample to prove the sharpness of the error bound $\tau$.

Connected through hyperedge HE-1 (induced by source paper "exact and robust reconstruction of integer vectors based on multidimensional chinese remainder theorem md crt"):
  with members:
    - "on solving ambiguity resolution with robust chinese remainder theorem for multiple numbers"
    - "towards robustness in residue number systems"
    - "selecting wavelengths for least squares range estimation"
    - "a robust generalized chinese remainder theorem for two integers"
    - "multi stage robust chinese remainder theorem"

Connected through hyperedge HE-2 (induced by source paper "robustness in chinese remainder theorem"):
  with members:
    - "towards robustness in residue number systems"
    - "a robust generalized chinese remainder theorem for two integers"
    - "multi stage robust chinese remainder theorem"

Connected through hyperedge HE-3 (induced by source paper "towards robustness in residue number systems"):
  with members:
    - "multi stage robust chinese remainder theorem"
    - "error correction in polynomial remainder codes with non pairwise coprime moduli and robust chinese remainder theorem for polynomials"

Connected through hyperedge HE-4 (induced by source paper "a robust generalized chinese remainder theorem for two integers"):
  with members:
    - "performance of ml range estimator in radio interferometric positioning systems"
    - "multi stage robust chinese remainder theorem"
    - "cryptanalyzing a class of image encryption schemes based on chinese remainder theorem"

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)