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 "universal almost optimal compression and slepian wolf coding in probabilistic polynomial time"):
  Abstract: In a lossless compression system with target lengths, a compressor ${\cal C}$ maps an integer $m$ and a binary string $x$ to an $m$-bit code $p$, and if $m$ is sufficiently large, a decompressor ${\cal D}$ reconstructs $x$ from $p$. We call a pair $(m,x)$ $\textit{achievable}$ for $({\cal C},{\cal D})$ if this reconstruction is successful. We introduce the notion of an optimal compressor ${\cal C}_\text{opt}$, by the following universality property: For any compressor-decompressor pair $({\cal C}, {\cal D})$, there exists a decompressor ${\cal D}'$ such that if $(m,x)$ is achievable for $({\cal C},{\cal D})$, then $(m+\Delta, x)$ is achievable for $({\cal C}_\text{opt}, {\cal D}')$, where $\Delta$ is some small value called the overhead. We show that there exists an optimal compressor that has only polylogarithmic overhead and works in probabilistic polynomial time. Differently said, for any pair $({\cal C}, {\cal D})$, no matter how slow ${\cal C}$ is, or even if ${\cal C}$ is non-computable, ${\cal C}_{\text{opt}}$ is a fixed compressor that in polynomial time produces codes almost as short as those of ${\cal C}$. The cost is that the corresponding decompressor is slower. #R##N#We also show that each such optimal compressor can be used for distributed compression, in which case it can achieve optimal compression rates, as given in the Slepian-Wolf theorem, and even for the Kolmogorov complexity variant of this theorem. Moreover, the overhead is logarithmic in the number of sources, and unlike previous implementations of Slepian-Wolf coding, meaningful compression can still be achieved if the number of sources is much larger than the length of the compressed strings.

Includes members:
  Member "coding in the fork network in the framework of kolmogorov complexity":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "distributed compression through the lens of algorithmic information theory a primer")
  Member "kolmogorov complexity version of slepian wolf coding":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "secret key agreement from correlated data with no prior information")
  Member "short lists with short programs in short time":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "how incomputable is kolmogorov complexity")
  Member "short lists with short programs in short time a short proof":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "how incomputable is kolmogorov complexity")
  Member "linear list approximation for short programs or the power of a few random bits":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "secret key agreement from correlated data with no prior information")
  Member "short lists for shortest descriptions in short time":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "optimal probabilistic polynomial time compression and the slepian wolf theorem tighter version and simple proofs")
  Member "variations on muchnik s conditional complexity theorem":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "secret key agreement from correlated data with no prior information")

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)