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 "a novel approach to multivariate redundancy and synergy"):
  Abstract: Consider a situation in which a set of $n$ "source" random variables $X_{1},\dots,X_{n}$ have information about some "target" random variable $Y$. For example, in neuroscience $Y$ might represent the state of an external stimulus and $X_{1},\dots,X_{n}$ the activity of $n$ different brain regions. Recent work in information theory has considered how to decompose the information that the sources $X_{1},\dots,X_{n}$ provide about the target $Y$ into separate terms such as (1) the "redundant information" that is shared among all of sources, (2) the "unique information" that is provided only by a single source, (3) the "synergistic information" that is provided by all sources only when considered jointly, and (4) the "union information" that is provided by at least one source. We propose a novel framework deriving such a decomposition that can be applied to any number of sources. Our measures are motivated in three distinct ways: via a formal analogy to intersection and union operators in set theory, via a decision-theoretic operationalization based on Blackwell's theorem, and via an axiomatic derivation. A key aspect of our approach is that we relax the assumption that measures of redundancy and union information should be related by the inclusion-exclusion principle. We discuss relations to previous proposals as well as possible generalizations.

Includes members:
  Member "understanding individual neuron importance using information theory":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on iterative neural network pruning reinitialization and the similarity of masks")
  Member "unique information and secret key agreement":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "an operational information decomposition via synergistic disclosure")
  Member "comparison of channels criteria for domination by a symmetric channel":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "on data processing and majorization inequalities for f divergences with applications")
  Member "pointwise partial information decomposition using the specificity and ambiguity lattices":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "an operational information decomposition via synergistic disclosure")
  Member "secret sharing and shared information":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "generalised measures of multivariate information content")
  Member "measuring multivariate redundant information with pointwise common change in surprisal":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "an operational information decomposition via synergistic disclosure")
  Member "quantifying synergistic information using intermediate stochastic variables":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "an operational information decomposition via synergistic disclosure")
  Member "on the input degradedness and input equivalence between channels":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "unique informations and deficiencies")

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)