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 coordinate system for gaussian networks"
  Abstract: This paper studies network information theory problems where the external noise is Gaussian distributed. In particular, the Gaussian broadcast channel with coherent fading and the Gaussian interference channel are investigated. It is shown that in these problems, non-Gaussian code ensembles can achieve higher rates than the Gaussian ones. It is also shown that the strong Shamai-Laroia conjecture on the Gaussian ISI channel does not hold. In order to analyze non-Gaussian code ensembles over Gaussian networks, a geometrical tool using the Hermite polynomials is proposed. This tool provides a coordinate system to analyze a class of non-Gaussian input distributions that are invariant over Gaussian networks.

Connected through hyperedge HE-1 (induced by source paper "on universal features for high dimensional learning and inference"):
  with members:
    - "on the sample complexity of hgr maximal correlation functions"
    - "probabilistic clustering using maximal matrix norm couplings"
    - "an information theoretic framework for non linear canonical correlation analysis"
    - "deep generalized canonical correlation analysis"
    - "strong data processing inequalities for channels and bayesian networks"
    - "robust subspace learning robust pca robust subspace tracking and robust subspace recovery"
    - "principal inertia components and applications"
    - "opening the black box of deep neural networks via information"

Connected through hyperedge HE-2 (induced by source paper "correlated embeddings of pairs of dependent random variables"):
  with members:
    - "on the sample complexity of hgr maximal correlation functions"
    - "a survey of multi view representation learning"
    - "an efficient approach to informative feature extraction from multimodal data"
    - "deep generalized canonical correlation analysis"
    - "a generalized power iteration method for solving quadratic problem on the stiefel manifold"
    - "deep variational canonical correlation analysis"
    - "principal inertia components and applications"
    - "tensorflow a system for large scale machine learning"

Connected through hyperedge HE-3 (induced by source paper "interference as noise friend or foe"):
  with members:
    - "on the two user interference channel with lack of knowledge of the interference codebook at one receiver"
    - "real interference alignment exploiting the potential of single antenna systems"
    - "on discrete alphabets for the two user gaussian interference channel with one receiver lacking knowledge of the interfering codebook"
    - "soft decoding based strategies for relay and interference channels analysis and achievable rates using ldpc codes"
    - "approximate sum capacity of k user cognitive interference channels with cumulative message sharing"
    - "the approximate sum capacity of the symmetric gaussian k user interference channel"
    - "wireless network information flow a deterministic approach"
    - "interference alignment from degrees of freedom to constant gap capacity approximations"

Connected through hyperedge HE-4 (induced by source paper "bounds between contraction coefficients"):
  with members:
    - "comparison of channels criteria for domination by a symmetric channel"
    - "f divergence inequalities"
    - "strong data processing inequalities for input constrained additive noise channels"
    - "information extraction under privacy constraints"
    - "tight bounds for symmetric divergence measures and a new inequality relating f divergences"
    - "dissipation of information in channels with input constraints"
    - "strong data processing inequalities and phi sobolev inequalities for discrete channels"
    - "linear information coupling problems"

Connected through hyperedge HE-5 (induced by source paper "euclidean information theory of networks"):
  with members:
    - "communication theoretic data analytics"
    - "linear information coupling problems"
    - "on maximal correlation hypercontractivity and the data processing inequality studied by erkip and cover"
    - "wireless network information flow a deterministic approach"
    - "feedback capacity of the gaussian interference channel to within 2 bits"

Connected through hyperedge HE-6 (induced by source paper "on the two user interference channel with lack of knowledge of the interference codebook at one receiver"):
  with members:
    - "on discrete alphabets for the two user gaussian interference channel with one receiver lacking knowledge of the interfering codebook"
    - "soft decoding based strategies for relay and interference channels analysis and achievable rates using ldpc codes"
    - "wireless network information flow a deterministic approach"
    - "the two user gaussian interference channel a deterministic view"
    - "gaussian interference channel capacity to within one bit"

Connected through hyperedge HE-7 (induced by source paper "lower bounds and approximations for the information rate of the isi channel"):
  with members:
    - "comparison of the achievable rates in ofdm and single carrier modulation with i i d inputs"
    - "easily computed lower bounds on the information rate of intersymbol interference channels"
    - "estimation in gaussian noise properties of the minimum mean square error"
    - "optimization of information rate upper and lower bounds for channels with memory"
    - "mutual information and minimum mean square error in gaussian channels"

Connected through hyperedge HE-8 (induced by source paper "two user interference channels with local views on capacity regions of tdm dominating policies"):
  with members:
    - "sum capacity of interference channels with a local view impact of distributed decisions"
    - "wireless network information flow a deterministic approach"
    - "on achieving local view capacity via maximal independent graph scheduling"
    - "the approximate capacity of the many to one and one to many gaussian interference channels"
    - "aiming perfectly in the dark blind interference alignment through staggered antenna switching"
    - "exploiting channel correlations simple interference alignment schemes with no csit"
    - "an axiomatic theory of fairness in network resource allocation"
    - "a new outer bound and the noisy interference sum rate capacity for gaussian interference channels"

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)