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: "polar lattices for lossy compression"
  Abstract: Polar lattices, which are constructed from polar codes, have recently been proved to be able to achieve the capacity of the additive white Gaussian noise (AWGN) channel. In this work, we propose a new construction of polar lattices to solve the dual problem, i.e., achieving the rate-distortion bound of a memoryless Gaussian source, which means that polar lattices can also be good for the lossy compression of continuous sources. The structure of the proposed polar lattices enables us to integrate the post-entropy coding process into the lattice quantizer, which simplifies the quantization process. The overall complexity of encoding and decoding complexity is $O(N \log^2 N)$ for a sub-exponentially decaying excess distortion. Moreover, the nesting structure of polar lattices further provides solutions for some multi-terminal coding problems. The Wyner-Ziv coding problem for a Gaussian source can be solved by an AWGN capacity-achieving polar lattice nested in a rate-distortion bound achieving one, and the Gelfand-Pinsker problem can be solved in a reversed manner.

Connected through hyperedge HE-1 (induced by source paper "polar codes and polar lattices for the heegard berger problem"):
  with members:
    - "polar codes for distributed hierarchical source coding"
    - "construction of capacity achieving lattice codes polar lattices"
    - "achieving awgn channel capacity with lattice gaussian coding"
    - "polar codes are optimal for lossy source coding"

Connected through hyperedge HE-2 (induced by source paper "extracting wyner s common information using polar codes and polar lattices"):
  with members:
    - "distributed simulation of continuous random variables"
    - "gaussian secure source coding and wyner s common information"
    - "construction of capacity achieving lattice codes polar lattices"
    - "the lossy common information of correlated sources"
    - "semantically secure lattice codes for the gaussian wiretap channel"
    - "achieving awgn channel capacity with lattice gaussian coding"
    - "achieving the capacity of any dmc using only polar codes"
    - "how to construct polar codes"

Connected through hyperedge HE-3 (induced by source paper "extracting wyner s common randomness using polar codes"):
  with members:
    - "polar lattices are good for lossy compression"
    - "the lossy common information of correlated sources"
    - "achieving awgn channel capacity with lattice gaussian coding"
    - "how to construct polar codes"
    - "channel polarization a method for constructing capacity achieving codes for symmetric binary input memoryless channels"

Connected through hyperedge HE-4 (induced by source paper "achieving secrecy capacity of the gaussian wiretap channel with polar lattices"):
  with members:
    - "covert communication over noisy channels a resolvability perspective"
    - "construction of capacity achieving lattice codes polar lattices"
    - "achieving secrecy capacity of the wiretap channel and broadcast channel with a confidential component"
    - "polar coding for the general wiretap channel"
    - "semantically secure lattice codes for the gaussian wiretap channel"
    - "how to achieve the capacity of asymmetric channels"
    - "achieving awgn channel capacity with lattice gaussian coding"
    - "secret key generation from gaussian sources using lattice hashing"

Connected through hyperedge HE-5 (induced by source paper "construction pi_a and pi_d lattices construction goodness and decoding algorithms"):
  with members:
    - "lda lattices without dithering achieve capacity on the gaussian channel"
    - "construction of capacity achieving lattice codes polar lattices"
    - "multistage compute and forward with multilevel lattice codes based on product constructions"
    - "lattices from codes for harnessing interference an overview and generalizations"
    - "lattices over eisenstein integers for compute and forward"
    - "connections between construction d and related constructions of lattices"
    - "a simple proof for the existence of good pairs of nested lattices"
    - "the approximate capacity of the many to one and one to many gaussian interference channels"

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)