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: "achieving the gaussian rate distortion function by prediction"
  Abstract: The "water-filling" solution for the quadratic rate-distortion function of a stationary Gaussian source is given in terms of its power spectrum. This formula naturally lends itself to a frequency domain "test-channel" realization. We provide an alternative time-domain realization for the rate-distortion function, based on linear prediction. This solution has some interesting implications, including the optimality at all distortion levels of pre/post filtered vector-quantized differential pulse code modulation (DPCM), and a duality relationship with decision-feedback equalization (DFE) for inter-symbol interference (ISI) channels.

Connected through hyperedge HE-1 (induced by source paper "the rate distortion function of asynchronously sampled memoryless cyclostationary gaussian processes"):
  with members:
    - "the capacity of memoryless channels with sampled cyclostationary gaussian noise"
    - "on the capacity of narrowband plc channels"
    - "the distortion rate function of cyclostationary gaussian processes"
    - "frequency shift filtering for ofdm signal recovery in narrowband power line communications"
    - "on the optimal compressions in the compress and forward relay schemes"
    - "the generalized asymptotic equipartition property necessary and sufficient conditions"

Connected through hyperedge HE-2 (induced by source paper "importance of small probability events in big data information measures applications and challenges"):
  with members:
    - "local deep feature alignment for unsupervised dimension reduction"
    - "matching users preference under target revenue constraints in data recommendation systems"
    - "differential message importance measure a new approach to the required sampling number in big data structure characterization"
    - "decorrelation of neutral vector variables theory and applications"
    - "group cooperation with optimal resource allocation in wireless powered communication networks"
    - "amplifying inter message distance on information divergence measures in big data"
    - "focusing on a probability element parameter selection of message importance measure in big data"
    - "linear complexity exponentially consistent tests for universal outlying sequence detection"

Connected through hyperedge HE-3 (induced by source paper "zero delay rate distortion via filtering for vector valued gaussian sources"):
  with members:
    - "an upper bound to zero delay rate distortion via kalman filtering for vector gaussian sources"
    - "filtering with fidelity for time varying gauss markov processes"
    - "a characterization of the minimal average data rate that guarantees a given closed loop performance level"
    - "nonanticipative rate distortion function and relations to filtering theory"
    - "directed information on abstract spaces properties and variational equalities"
    - "improved upper bounds to the causal quadratic rate distortion function for gaussian stationary sources"

Connected through hyperedge HE-4 (induced by source paper "fundamental distortion limits of analog to digital compression"):
  with members:
    - "distortion rate function of sub nyquist sampled gaussian sources"
    - "sampling rate distortion"
    - "indirect rate distortion function of a binary i i d source"
    - "channel capacity under sub nyquist nonuniform sampling"
    - "sampling and distortion tradeoffs for bandlimited periodic signals"
    - "shannon meets nyquist capacity of sampled gaussian channels"
    - "lossy computing of correlated sources with fractional sampling"
    - "optimal phase transitions in compressed sensing"

Connected through hyperedge HE-5 (induced by source paper "sampling stationary signals subject to bitrate constraints"):
  with members:
    - "distortion rate function of sub nyquist sampled gaussian sources"
    - "channel capacity under sub nyquist nonuniform sampling"
    - "optimal phase transitions in compressed sensing"

Connected through hyperedge HE-6 (induced by source paper "performance analysis and optimal filter design for sigma delta modulation via duality with dpcm"):
  with members:
    - "interactive schemes for the awgn channel with noisy feedback"
    - "the gaussian channel with noisy feedback near capacity performance via simple interaction"
    - "precoded integer forcing universally achieves the mimo capacity to within a constant gap"
    - "improved upper bounds to the causal quadratic rate distortion function for gaussian stationary sources"
    - "multiple description coding by dithered delta sigma quantization"

Connected through hyperedge HE-7 (induced by source paper "fundamental inequalities and identities involving mutual and directed informations in closed loop systems"):
  with members:
    - "the information flow and capacity of channels with noisy feedback"
    - "data processing inequalities based on a certain structured class of information measures with application to estimation theory"
    - "a new data processing inequality and its applications in distributed source and channel coding"
    - "improved upper bounds to the causal quadratic rate distortion function for gaussian stationary sources"
    - "interpretations of directed information in portfolio theory data compression and hypothesis testing"
    - "a coding theorem for a class of stationary channels with feedback"
    - "the capacity of channels with feedback"

Connected through hyperedge HE-8 (induced by source paper "on constrained randomized quantization"):
  with members:
    - "scalar quantization with random thresholds"
    - "gossip algorithms for distributed signal processing"
    - "distributed consensus algorithms in sensor networks quantized data and random link failures"
    - "multiple description coding by dithered delta sigma quantization"

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)