human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "low complexity algorithms for transmission of short blocks over the bsc with full feedback"):
  Abstract: Building on the work of Horstein, Shayevitz and Feder, and Naghshvar et al., this paper presents algorithms for low-complexity sequential transmission of a $k$-bit message over the binary symmetric channel (BSC) with full, noiseless feedback. To lower complexity, this paper shows that the initial $k$ binary transmissions can be sent before any feedback is required and groups the messages with equal posteriors to reduce the number of posterior updates from exponential in $k$ to linear in $k$. Simulations results demonstrate the achievable rates for this full, noiseless feedback system approach capacity rapidly as a function of $k$, significantly faster than the achievable rate curve of Polyanskiy et al. for a stop feedback system.

Includes members:
  Member "finite blocklength performance of sequential transmission over bsc with noiseless feedback":
    also connected through other hyperedges:
      (none)
  Member "variable length convolutional coding for short blocklengths with decision feedback":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "short packet transmission via variable length codes in the presence of noisy stop feedback")
  Member "extrinsic jensen shannon divergence applications to variable length coding":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "decentralized sequential active hypothesis testing and the mac feedback capacity")
  Member "optimal feedback communication via posterior matching":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "feedback channel communication with low precision arithmetic")

Question: Please tell me which class the source paper 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)