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: "achieving the empirical capacity using feedback part i memoryless additive models"
  Abstract: We address the problem of universal communications over an unknown channel with an instantaneous noiseless feedback, and show how rates corresponding to the empirical behavior of the channel can be attained, although no rate can be guaranteed in advance. First, we consider a discrete modulo-additive channel with alphabet $\mathcal{X}$, where the noise sequence $Z^n$ is arbitrary and unknown and may causally depend on the transmitted and received sequences and on the encoder's message, possibly in an adversarial fashion. Although the classical capacity of this channel is zero, we show that rates approaching the empirical capacity $\log|\mathcal{X}|-H_{emp}(Z^n)$ can be universally attained, where $H_{emp}(Z^n)$ is the empirical entropy of $Z^n$. For the more general setting where the channel can map its input to an output in an arbitrary unknown fashion subject only to causality, we model the empirical channel actions as the modulo-addition of a realized noise sequence, and show that the same result applies if common randomness is available. The results are proved constructively, by providing a simple sequential transmission scheme approaching the empirical capacity. In part II of this work we demonstrate how even higher rates can be attained by using more elaborate models for channel actions, and by utilizing possible empirical dependencies in its behavior.

Connected through hyperedge HE-1 (induced by source paper "the porosity of additive noise sequences"):
  with members:
    - "zero rate feedback can achieve the empirical capacity"

Connected through hyperedge HE-2 (induced by source paper "universal communication over arbitrarily varying channels"):
  with members:
    - "communication over individual channels"
    - "zero rate feedback can achieve the empirical capacity"
    - "universal communication part i modulo additive channels"

Connected through hyperedge HE-3 (induced by source paper "an achievable rate for the mimo individual channel"):
  with members:
    - "communication over individual channels"
    - "zero rate feedback can achieve the empirical capacity"
    - "feedback communication over individual channels"

Connected through hyperedge HE-4 (induced by source paper "power adaptive feedback communication over an additive individual noise sequence channel"):
  with members:
    - "communication over individual channels"
    - "zero rate feedback can achieve the empirical capacity"
    - "feedback communication over individual channels"

Connected through hyperedge HE-5 (induced by source paper "feedback communication over individual channels"):
  with members:
    - "communication over individual channels"
    - "zero rate feedback can achieve the empirical capacity"
    - "coding into a source a direct inverse rate distortion theorem"

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)