human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "multiterminal source coding under logarithmic loss"
  Abstract: We consider the classical two-encoder multiterminal source coding problem where distortion is measured under logarithmic loss. We provide a single-letter characterization of the achievable rate distortion region for arbitrarily correlated sources with finite alphabets. In doing so, we also give the rate distortion region for the $m$-encoder CEO problem (also under logarithmic loss). Several applications and examples are given.

Connected through hyperedge HE-1 (induced by source paper "on the information bottleneck problems models connections applications and information theoretic views"):
  with members:
    - "learning representations for neural network based classification using the information bottleneck principle"
    - "machine learning using the variational predictive information bottleneck with a validation set"
    - "on the difference between the information bottleneck and the deep information bottleneck"
    - "extracting robust and accurate features via a robust information bottleneck"
    - "general information bottleneck objectives and their applications to machine learning"
    - "vector gaussian ceo problem under logarithmic loss"
    - "on universal features for high dimensional learning and inference"
    - "estimation efficiency under privacy constraints"

Connected through hyperedge HE-2 (induced by source paper "exponential strong converse for successive refinement with causal decoder side information"):
  with members:
    - "strong converse using change of measure arguments"
    - "exponential strong converse for content identification with lossy recovery"
    - "discrete lossy gray wyner revisited second order asymptotics large and moderate deviations"
    - "new strong converse for asymmetric broadcast channels"
    - "a proof of the strong converse theorem for gaussian multiple access channels"
    - "exponent function for one helper source coding problem at rates outside the rate region"
    - "strong successive refinability and rate distortion complexity tradeoff"
    - "asymptotic estimates in information theory with non vanishing error probabilities"

Connected through hyperedge HE-3 (induced by source paper "vector gaussian ceo problem under logarithmic loss"):
  with members:
    - "vector gaussian ceo problem under logarithmic loss and applications"
    - "universality of logarithmic loss in lossy compression"
    - "on the optimal fronthaul compression and decoding strategies for uplink cloud radio access networks"
    - "justification of logarithmic loss via the benefit of side information"
    - "rate region of the vector gaussian ceo problem with the trace distortion constraint"
    - "secure source coding with a public helper"
    - "an outer bound for the vector gaussian ceo problem"
    - "multiterminal source coding with an entropy based distortion measure"

Connected through hyperedge HE-4 (induced by source paper "optimal rate exponent region for a class of hypothesis testing against conditional independence problems"):
  with members:
    - "distributed hypothesis testing with concurrent detections"
    - "on hypothesis testing against independence with multiple decision centers"
    - "hypothesis testing under maximal leakage privacy constraints"
    - "an outer bound for the vector gaussian ceo problem"
    - "rate region of the quadratic gaussian two encoder source coding problem"

Connected through hyperedge HE-5 (induced by source paper "fundamental limits of distributed tracking"):
  with members:
    - "rate cost tradeoffs in control"
    - "a characterization of the minimal average data rate that guarantees a given closed loop performance level"
    - "improved upper bounds to the causal quadratic rate distortion function for gaussian stationary sources"
    - "successive wyner ziv coding scheme and its application to the quadratic gaussian ceo problem"
    - "rate region of the quadratic gaussian two encoder source coding problem"

Connected through hyperedge HE-6 (induced by source paper "tunable measures for information leakage and applications to privacy utility tradeoffs"):
  with members:
    - "robustness of maximal alpha leakage to side information"
    - "data privacy for a rho recoverable function"
    - "an operational approach to information leakage"
    - "optimal utility privacy trade off with the total variation distance as the privacy measure"
    - "robust privacy utility tradeoffs under differential privacy and hamming distortion"
    - "privacy aware guessing efficiency"
    - "renyi differential privacy"
    - "hypothesis testing under mutual information privacy constraints in the high privacy regime"

Connected through hyperedge HE-7 (induced by source paper "vector gaussian ceo problem under logarithmic loss and applications"):
  with members:
    - "vector gaussian ceo problem under logarithmic loss"
    - "chaining mutual information and tightening generalization bounds"
    - "on the universality of the logistic loss function"
    - "minimax learning for remote prediction"
    - "information theoretic analysis of generalization capability of learning algorithms"
    - "distributed information bottleneck method for discrete and gaussian sources"
    - "universality of logarithmic loss in lossy compression"
    - "a generalization of blahut arimoto algorithm to compute rate distortion regions of multiterminal source coding under logarithmic loss"

Connected through hyperedge HE-8 (induced by source paper "generalized compression strategy for the downlink cloud radio access network"):
  with members:
    - "hybrid data sharing and compression strategy for downlink cloud radio access network"
    - "on the optimal fronthaul compression and decoding strategies for uplink cloud radio access networks"
    - "an uplink downlink duality for cloud radio access network"
    - "on achievability for downlink cloud radio access networks with base station cooperation"
    - "cloud radio access network virtualizing wireless access for dense heterogeneous systems"
    - "distributed decode forward for relay networks"
    - "sparse beamforming and user centric clustering for downlink cloud radio access network"
    - "joint precoding and multivariate backhaul compression for the downlink of cloud radio access networks"

Question: Please tell me which class the center node 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)