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 "improved target acquisition rates with feedback codes"):
  Abstract: This paper considers the problem of acquiring an unknown target location (among a finite number of locations) via a sequence of measurements, where each measurement consists of simultaneously probing a group of locations. The resulting observation consists of a sum of an indicator of the target's presence in the probed region, and a zero mean Gaussian noise term whose variance is a function of the measurement vector. An equivalence between the target acquisition problem and channel coding over a binary input additive white Gaussian noise (BAWGN) channel with state and feedback is established. Utilizing this information theoretic perspective, a two-stage adaptive target search strategy based on the sorted Posterior Matching channel coding strategy is proposed. Furthermore, using information theoretic converses, the fundamental limits on the target acquisition rate for adaptive and non-adaptive strategies are characterized. As a corollary to the non-asymptotic upper bound of the expected number of measurements under the proposed two-stage strategy, and to non-asymptotic lower bound of the expected number of measurements for optimal non-adaptive search strategy, a lower bound on the adaptivity gain is obtained. The adaptivity gain is further investigated in different asymptotic regimes of interest.

Includes members:
  Member "comparative analysis of initial access techniques in 5g mmwave cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on optimal multi user beam alignment in millimeter wave wireless systems")
  Member "directional initial access for millimeter wave cellular systems":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a tutorial on beam management for 3gpp nr at mmwave frequencies")
  Member "extrinsic jensen shannon divergence applications to variable length coding":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "low complexity algorithms for transmission of short blocks over the bsc with full feedback")
  Member "searching with measurement dependent noise":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "active learning and csi acquisition for mmwave initial alignment")
  Member "collaborative 20 questions for target localization":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "construction and analysis of posterior matching in arbitrary dimensions via optimal transport")
  Member "near optimal adaptive compressed sensing":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "efficient active learning of sparse halfspaces with arbitrary bounded noise")
  Member "optimal multiband joint detection for spectrum sensing in cognitive radio networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "optimization of the belief propagation algorithm for distributed detection by linear data fusion techniques")

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)