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: "extension of the blahut arimoto algorithm for maximizing directed information"
  Abstract: We extend the Blahut-Arimoto algorithm for maximizing Massey's directed information. The algorithm can be used for estimating the capacity of channels with delayed feedback, where the feedback is a deterministic function of the output. In order to do so, we apply the ideas from the regular Blahut-Arimoto algorithm, i.e., the alternating maximization procedure, onto our new problem. We provide both upper and lower bound sequences that converge to the optimum value. Our main insight in this paper is that in order to find the maximum of the directed information over causal conditioning probability mass function (PMF), one can use a backward index time maximization combined with the alternating maximization procedure. We give a detailed description of the algorithm, its complexity, the memory needed, and several numerical examples.

Connected through hyperedge HE-1 (induced by source paper "analysis for the slow convergence in arimoto algorithm"):
  with members:
    - "on the search algorithm for the output distribution that achieves the channel capacity"
    - "squeezing the arimoto blahut algorithm for faster convergence"
    - "geometrical interpretation and improvements of the blahut arimoto s algorithm"

Connected through hyperedge HE-2 (induced by source paper "capacity analysis of discrete energy harvesting channels"):
  with members:
    - "capacity of the energy harvesting channel with a finite battery"
    - "can feedback increase the capacity of the energy harvesting channel"
    - "capacity of a post channel with and without feedback"
    - "a randomized approach to the capacity of finite state channels"
    - "binary energy harvesting channel with finite energy storage"
    - "awgn channel under time varying amplitude constraints with causal information at the transmitter"
    - "optimum transmission policies for battery limited energy harvesting nodes"
    - "optimal packet scheduling in an energy harvesting communication system"

Connected through hyperedge HE-3 (induced by source paper "analogy between gambling and measurement based work extraction"):
  with members:
    - "interpretations of directed information in portfolio theory data compression and hypothesis testing"
    - "finite state channels with time invariant deterministic feedback"

Connected through hyperedge HE-4 (induced by source paper "directed information on abstract spaces properties and variational equalities"):
  with members:
    - "sequential necessary and sufficient conditions for capacity achieving distributions of channels with memory and feedback"
    - "capacity achieving distributions information lossless randomized strategies for feedback channels with memory the lqg theory of directed information part ii"
    - "optimal nonanticipative estimation schemes for time varying gauss markov processes"
    - "capacity of binary state symmetric channel with and without feedback and transmission cost"
    - "information nonanticipative rate distortion function and its applications"
    - "information structures for feedback capacity of channels with memory and transmission cost stochastic optimal control variational equalities part i"
    - "nonanticipative rate distortion function and relations to filtering theory"
    - "capacity of a post channel with and without feedback"

Connected through hyperedge HE-5 (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"
    - "computable bounds for rate distortion with feed forward for stationary and ergodic sources"
    - "improved upper bounds to the causal quadratic rate distortion function for gaussian stationary sources"
    - "on delayed sequential coding of correlated sources"

Connected through hyperedge HE-6 (induced by source paper "capacity of a post channel with and without feedback"):
  with members:
    - "no input symbol should occur more frequently than 1 1 e"
    - "capacity and coding for the ising channel with feedback"
    - "a coding theorem for a class of stationary channels with feedback"
    - "finite state channels with time invariant deterministic feedback"
    - "feedback capacity of stationary gaussian channels"
    - "the capacity of channels with feedback"

Connected through hyperedge HE-7 (induced by source paper "channel coding and source coding with increased partial side information"):
  with members:
    - "computable bounds for rate distortion with feed forward for stationary and ergodic sources"
    - "duality between channel capacity and rate distortion with two sided state information"

Connected through hyperedge HE-8 (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"
    - "computable bounds for rate distortion with feed forward for stationary and ergodic sources"
    - "directed information and pearl s causal calculus"

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)