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: "zero delay rate distortion via filtering for unstable vector gaussian sources"
  Abstract: In this work, we deal with zero-delay source coding of an unstable vector Gaussian Auto-Regressive (AR) source under average mean square error fidelity criterion. To begin with, we consider zero-delay coding of a vector Gaussian AR(1) source modeled in state space form. It turns out to be convenient to use an asymptotically stationary time-domain scheme with feedback, which was recently proposed in [1] in the context of filtering theory applications via the Information Nonanticipative Rate Distortion Function (INRDF). In this scheme, the feedback path comprises a Kalman filter, which produces an estimate of the source. Our idea is then to encode the vector innovations due to Kalman filtering via lattice quantization with subtractive dither and memoryless entropy coding. We show that the resulting system is stable and furthermore provide new bounds to the zero-delay RDF. We then generalize our results to vector Gaussian AR sources of any order. With this, we are able to establish a time-domain approach with feedback, which by use of a single filter gets very close to the zero-delay RDF for vector Gaussian AR sources of any order. Interestingly, for infinite dimensional vector sources, the INRDF coincides with the Optimal Performance Theoretically Attainable (OPTA) by zero-delay codes.

Connected through hyperedge HE-1 (induced by source paper "sequential empirical coordination under an output entropy constraint"):
  with members:
    - "information theoretic approach to strategic communication as a hierarchical game"
    - "empirical processes typical sequences and coordinated actions in standard borel spaces"
    - "channel simulation via interactive communications"
    - "the capacity of channels with feedback"

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)