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 random variable substitution lemma with applications to multiple description coding"):
  Abstract: We establish a random variable substitution lemma and use it to investigate the role of refinement layer in multiple description coding, which clarifies the relationship among several existing achievable multiple description rate-distortion regions. Specifically, it is shown that the El Gamal-Cover (EGC) region is equivalent to the EGC* region (an antecedent version of the EGC region) while the Venkataramani-Kramer-Goyal (VKG) region (when specialized to the 2-description case) is equivalent to the Zhang-Berger (ZB) region. Moreover, we prove that for multiple description coding with individual and hierarchical distortion constraints, the number of layers in the VKG scheme can be significantly reduced when only certain weighted sum rates are concerned. The role of refinement layer in scalable coding (a special case of multiple description coding) is also studied.

Includes members:
  Member "approximating the gaussian multiple description rate region under symmetric distortion constraints":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on the storage cost of private information retrieval")
  Member "vector gaussian multiple description with individual and central receivers":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "vector gaussian successive refinement with degraded side 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)