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 "properties of unique information"):
  Abstract: We study the measure of unique information $UI(T:X\setminus Y)$ defined by Bertschinger et al. (2014) within the framework of information decompositions. We study uniqueness and support of the solutions to the optimization problem underlying the definition of $UI$. We give necessary conditions for non-uniqueness of solutions with full support in terms of the cardinalities of $T$, $X$ and $Y$ and in terms of conditional independence constraints. Our results help to speed up the computation of $UI(T:X\setminus Y)$, most notably in the case where $T$ is binary. In the case that all variables are binary, we obtain a complete picture where the optimizing probability distributions lie.

Includes members:
  Member "computing the unique information":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "an operational information decomposition via synergistic disclosure")
  Member "pointwise partial information decomposition using the specificity and ambiguity lattices":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "an operational information decomposition via synergistic disclosure")
  Member "measuring multivariate redundant information with pointwise common change in surprisal":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "an operational information decomposition via synergistic disclosure")
  Member "reconsidering unique information towards a multivariate information decomposition":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "an operational information decomposition via synergistic disclosure")
  Member "bivariate measure of redundant information":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "an operational information decomposition via synergistic disclosure")
  Member "nonnegative decomposition of multivariate information":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "an operational information decomposition via synergistic disclosure")

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)