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: "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.

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)