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: "optimal estimation via nonanticipative rate distortion function and applications to time varying gauss markov processes"
  Abstract: In this paper, we develop {finite-time horizon} causal filters using the nonanticipative rate distortion theory. We apply the {developed} theory to {design optimal filters for} time-varying multidimensional Gauss-Markov processes, subject to a mean square error fidelity constraint. We show that such filters are equivalent to the design of an optimal \texttt{\{encoder, channel, decoder\}}, which ensures that the error satisfies {a} fidelity constraint. Moreover, we derive a universal lower bound on the mean square error of any estimator of time-varying multidimensional Gauss-Markov processes in terms of conditional mutual information. Unlike classical Kalman filters, the filter developed is characterized by a reverse-waterfilling algorithm, which ensures {that} the fidelity constraint is satisfied. The theoretical results are demonstrated via illustrative examples.

Connected through hyperedge HE-1 (induced by source paper "a converse bound characterization on zero delay indirect rdf for vector gauss markov sources"):
  with members:
    - "zero delay rate distortion via filtering for vector valued gaussian sources"
    - "directed information on abstract spaces properties and variational equalities"
    - "internet of things iot a vision architectural elements and future directions"
    - "improved upper bounds to the causal quadratic rate distortion function for gaussian stationary sources"

Connected through hyperedge HE-2 (induced by source paper "optimal causal rate constrained sampling of the wiener process"):
  with members:
    - "remote estimation of the wiener process over a channel with random delay"
    - "event triggered stabilization of linear systems under bounded bit rates"
    - "infinite horizon optimal transmission power control for remote state estimation over fading channels"
    - "the distortion rate function of sampled wiener processes"
    - "rate cost tradeoffs in control"
    - "event triggered control under time varying rates and channel blackouts"
    - "optimal estimation with limited measurements and noisy communication"
    - "optimal strategies for communication and remote estimation with an energy harvesting sensor"

Connected through hyperedge HE-3 (induced by source paper "on zero delay rdf for vector valued gauss markov sources with additional noise"):
  with members:
    - "zero delay rate distortion via filtering for vector valued gaussian sources"
    - "indirect rate distortion function of a binary i i d source"
    - "directed information on abstract spaces properties and variational equalities"
    - "internet of things iot a vision architectural elements and future directions"
    - "improved upper bounds to the causal quadratic rate distortion function for gaussian stationary sources"

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)