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: "fixed length lossy compression in the finite blocklength regime"
  Abstract: This paper studies the minimum achievable source coding rate as a function of blocklength n and probability ϵ that the distortion exceeds a given level d . Tight general achievability and converse bounds are derived that hold at arbitrary fixed blocklength. For stationary memoryless sources with separable distortion, the minimum rate achievable is shown to be closely approximated by R(d) + √V(d)/(n) Q-1(ϵ), where R(d) is the rate-distortion function, V(d) is the rate dispersion, a characteristic of the source which measures its stochastic variability, and Q-1(·) is the inverse of the standard Gaussian complementary cumulative distribution function.

Connected through hyperedge HE-1 (induced by source paper "finite sample analysis of image registration"):
  with members:
    - "estimators for multivariate information measures in general probability spaces"
    - "end to end unsupervised deformable image registration with a convolutional neural network"
    - "a deep metric for multimodal registration"
    - "fundamental limits in multi image alignment"
    - "demystifying fixed k nearest neighbor information estimators"
    - "asymptotic estimates in information theory with non vanishing error probabilities"
    - "asymptotics and non asymptotics for universal fixed to variable source coding"
    - "channels with cost constraints strong converse and dispersion"

Connected through hyperedge HE-2 (induced by source paper "one shot approach to lossy source coding under average distortion constraints"):
  with members:
    - "achievable and converse bounds over a general channel and general decoding metric"
    - "lossy joint source channel coding in the finite blocklength regime"

Connected through hyperedge HE-3 (induced by source paper "polar codes simplicity random codes durability"):
  with members:
    - "reed muller codes polarize"
    - "ar i kan meets shannon polar codes with near optimal convergence to channel capacity"
    - "explicit polar codes with small scaling exponent"
    - "on the capacity of channels with deletions and states"
    - "polar codes for the deletion channel weak and strong polarization"
    - "polar like codes and asymptotic tradeoff among block length code rate and error probability"
    - "scaling exponent and moderate deviations asymptotics of polar codes for the awgn channel"
    - "relaxed polar codes"

Connected through hyperedge HE-4 (induced by source paper "sparse regression codes"):
  with members:
    - "the error probability of sparse superposition codes with approximate message passing decoding"
    - "sparcs for unsourced random access"
    - "spatially coupled sparse regression codes design and state evolution analysis"
    - "techniques for improving the finite length performance of sparse superposition codes"
    - "approximate message passing decoder and capacity achieving sparse superposition codes"
    - "capacity achieving sparse superposition codes via approximate message passing decoding"
    - "the rate distortion function and excess distortion exponent of sparse regression codes with optimal encoding"
    - "universal sparse superposition codes with spatial coupling and gamp decoding"

Connected through hyperedge HE-5 (induced by source paper "learning to compress and search visual data in large scale systems"):
  with members:
    - "rendition reclaiming what a black box takes away"
    - "polysemous codes"
    - "soft to hard vector quantization for end to end learning compressible representations"
    - "billion scale similarity search with gpus"
    - "hashnet deep learning to hash by continuation"
    - "memnet a persistent memory network for image restoration"
    - "full resolution image compression with recurrent neural networks"
    - "end to end optimized image compression"

Connected through hyperedge HE-6 (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-7 (induced by source paper "lossless source coding in the point to point multiple access and random access scenarios"):
  with members:
    - "random access channel coding in the finite blocklength regime"
    - "on the calculation of the minimax converse of the channel coding problem"
    - "on the dispersions of three network information theory problems"
    - "variable length compression allowing errors"
    - "random access an information theoretic perspective"
    - "lossy joint source channel coding in the finite blocklength regime"
    - "second order slepian wolf coding theorems for non mixed and mixed sources"
    - "network coding is zero error always possible"

Connected through hyperedge HE-8 (induced by source paper "from parameter estimation to dispersion of nonstationary gauss markov processes"):
  with members:
    - "the dispersion of the gauss markov source"
    - "non asymptotic identification of lti systems from a single trajectory"
    - "near optimal finite time identification of arbitrary linear dynamical systems"
    - "learning without mixing towards a sharp analysis of linear system identification"
    - "finite time identification in unstable linear systems"
    - "the dispersion of lossy source coding"
    - "a note on rate distortion functions for nonstationary gaussian autoregressive processes"

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)