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: "computable bounds for rate distortion with feed forward for stationary and ergodic sources"
  Abstract: In this paper we consider the rate distortion problem of discrete-time, ergodic, and stationary sources with feed forward at the receiver. We derive a sequence of achievable and computable rates that converge to the feed-forward rate distortion. We show that, for ergodic and stationary sources, the rate {align} R_n(D)=\frac{1}{n}\min I(\hat{X}^n\rightarrow X^n){align} is achievable for any $n$, where the minimization is taken over the transition conditioning probability $p(\hat{x}^n|x^n)$ such that $\ex{}{d(X^n,\hat{X}^n)}\leq D$. The limit of $R_n(D)$ exists and is the feed-forward rate distortion. We follow Gallager's proof where there is no feed-forward and, with appropriate modification, obtain our result. We provide an algorithm for calculating $R_n(D)$ using the alternating minimization procedure, and present several numerical examples. We also present a dual form for the optimization of $R_n(D)$, and transform it into a geometric programming problem.

Connected through hyperedge HE-1 (induced by source paper "variational equalities of directed information and applications"):
  with members:
    - "nonanticipative rate distortion function and relations to filtering theory"
    - "directed information on abstract spaces properties and variational equalities"
    - "nonanticipative rate distortion function for general source channel matching"
    - "directed information on abstract spaces properties and extremum problems"
    - "nonanticipative rate distortion function and filtering theory a weak convergence approach"
    - "improved upper bounds to the causal quadratic rate distortion function for gaussian stationary sources"
    - "extension of the blahut arimoto algorithm for maximizing directed information"
    - "on delayed sequential coding of correlated sources"

Connected through hyperedge HE-2 (induced by source paper "channel coding and source coding with increased partial side information"):
  with members:
    - "extension of the blahut arimoto algorithm for maximizing directed information"
    - "duality between channel capacity and rate distortion with two sided state information"

Connected through hyperedge HE-3 (induced by source paper "directed information graphs"):
  with members:
    - "justification of logarithmic loss via the benefit of side information"
    - "causal networks semantics and expressiveness"
    - "universal estimation of directed information"
    - "causal conditioning and instantaneous coupling in causality graphs"
    - "the relation between granger causality and directed information theory a review"
    - "information theoretic measures of influence based on content dynamics"
    - "directed information and pearl s causal calculus"
    - "causal dependence tree approximations of joint distributions for multiple random processes"

Connected through hyperedge HE-4 (induced by source paper "source coding when the side information may be delayed"):
  with members:
    - "interpretations of directed information in portfolio theory data compression and hypothesis testing"
    - "on successive refinement for the kaspi heegard berger problem"
    - "coding for the feedback gel fand pinsker channel and the feedforward wyner ziv source"

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)