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 "resolution limits of noisy 20 questions estimation"):
  Abstract: We establish fundamental limits on estimation accuracy for the noisy 20 questions problem with measurement dependent noise and introduce optimal non-adaptive procedures that achieve this limits. The minimal achievable resolution is defined as the absolute difference between the estimated and the true values of the target random variable, given a finite number of queries constrained by the excess-resolution probability. Inspired by the relationship between the 20 questions problem and the channel coding problem, we derive non-asymptotic bounds on the minimal achievable resolution. Furthermore, applying the Berry-Esseen theorem to our non-asymptotic bounds, we obtain a second-order asymptotic approximation to finite blocklength performance, specifically the achievable resolution of optimal non-adaptive query procedures with a finite number of queries subject to the excess-resolution probability constraint. We specialize our second-order results to measurement dependent versions of several channel models including the binary symmetric, the binary erasure and the binary Z- channels. Our results are then extended to adaptive query procedures, establishing a lower bound on the resolution gain associated with adaptive querying.

Includes members:
  Member "unequal error protection querying policies for the noisy 20 questions problem":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "parity queries for binary classification")
  Member "improved target acquisition rates with feedback codes":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "active learning and csi acquisition for mmwave initial alignment")
  Member "exponential strong converse for content identification with lossy recovery":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "exponential strong converse for successive refinement with causal decoder side information")
  Member "smoothing brascamp lieb inequalities and strong converses for common randomness generation":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "communication complexity of estimating correlations")
  Member "asymptotic estimates in information theory with non vanishing error probabilities":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "finite sample analysis of image registration")
  Member "the dispersion of nearest neighbor decoding for additive non gaussian channels":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "coexistence mechanism between embb and urllc in 5g wireless networks")
  Member "second order coding rates for channels with state":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "second order and moderate deviation analysis of a block fading channel with deterministic and energy harvesting power constraints")
  Member "searching with measurement dependent noise":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "active learning and csi acquisition for mmwave initial alignment")

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)