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 "searching with measurement dependent noise"):
  Abstract: Consider a target moving with a constant velocity on a unit-circumference circle, starting from an arbitrary location. To acquire the target, any region of the circle can be probed for its presence, but the associated measurement noise increases with the size of the probed region. We are interested in the expected time required to find the target to within some given resolution and error probability. For a known velocity, we characterize the optimal tradeoff between time and resolution (i.e., maximal rate), and show that in contrast to the case of constant measurement noise, measurement dependent noise incurs a multiplicative gap between adaptive search and non-adaptive search. Moreover, our adaptive scheme attains the optimal rate-reliability tradeoff. We further show that for optimal non-adaptive search, accounting for an unknown velocity incurs a factor of two in rate.

Includes members:
  Member "a simple proof for the optimality of randomized posterior matching":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "active learning and csi acquisition for mmwave initial alignment")
  Member "extrinsic jensen shannon divergence applications to variable length coding":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "low complexity algorithms for transmission of short blocks over the bsc with full feedback")
  Member "collaborative 20 questions for target localization":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "construction and analysis of posterior matching in arbitrary dimensions via optimal transport")
  Member "boolean compressed sensing and noisy group testing":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "serial quantization for sparse time sequences")
  Member "communication over individual channels":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "robust gaussian joint source channel coding with a staircase distortion noise profile")
  Member "interference mitigation in large random wireless networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "group testing an information theory perspective")
  Member "zero rate feedback can achieve the empirical capacity":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "learning an adversary s actions for secret communication")
  Member "optimal feedback communication via posterior matching":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "feedback channel communication with low precision arithmetic")

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)