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 "optimal algorithms for universal random number generation from finite memory sources"):
  Abstract: We study random number generators (RNGs), both in the fixed to variable-length (FVR) and the variable to fixed-length (VFR) regimes, in a universal setting in which the input is a finite memory source of arbitrary order and unknown parameters, with arbitrary input and output (finite) alphabet sizes. Applying the method of types, we characterize essentially unique optimal universal RNGs that maximize the expected output (respectively, minimize the expected input) length in the FVR (respectively, VFR) case. For the FVR case, the RNG studied is a generalization of Elias's scheme, while in the VFR case the general scheme is new. We precisely characterize, up to an additive constant, the corresponding expected lengths, which include second-order terms similar to those encountered in universal data compression and universal simulation. Furthermore, in the FVR case, we consider also a twice-universal setting, in which the Markov order k of the input source is also unknown.

Includes members:
  Member "a universal scheme for transforming binary algorithms to generate random bits from loaded dice":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "streaming algorithms for optimal generation of random bits")
  Member "efficient generation of random bits from finite state markov chains":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "streaming algorithms for optimal generation of random bits")
  Member "fast enumeration of combinatorial objects":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "asymptotically optimum perfect universal steganography of finite memoryless sources")

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)