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: "incremental and decremental secret key agreement"
  Abstract: We study the rate of change of the multivariate mutual information among a set of random variables when some common randomness is added to or removed from a subset. This is formulated more precisely as two new multiterminal secret key agreement problems which ask how one can increase the secrecy capacity efficiently by adding common randomness to a small subset of users, and how one can simplify the source model by removing redundant common randomness that does not contribute to the secrecy capacity. The combinatorial structure has been clarified along with some meaningful open problems.

Connected through hyperedge HE-1 (induced by source paper "secret key agreement for hypergraphical sources with limited total discussion"):
  with members:
    - "multiterminal secret key agreement with nearly no discussion"
    - "one shot perfect secret key agreement for finite linear sources"
    - "secrecy capacity under limited discussion rate for minimally connected hypergraphical sources"
    - "upper bounds via lamination on the constrained secrecy capacity of hypergraphical sources"
    - "multiterminal secret key agreement at asymptotically zero discussion rate"
    - "secret key agreement under discussion rate constraints"
    - "compressed secret key agreement maximizing multivariate mutual information per bit"
    - "on the optimality of secret key agreement via omniscience"

Connected through hyperedge HE-2 (induced by source paper "multiterminal secret key agreement with nearly no discussion"):
  with members:
    - "upper bounds via lamination on the constrained secrecy capacity of hypergraphical sources"
    - "multiterminal secret key agreement at asymptotically zero discussion rate"
    - "secret key agreement under discussion rate constraints"
    - "compressed secret key agreement maximizing multivariate mutual information per bit"
    - "on the optimality of secret key agreement via omniscience"
    - "bounds on the communication rate needed to achieve sk capacity in the hypergraphical source model"
    - "secret key generation with limited interaction"
    - "info clustering a mathematical theory for data clustering"

Connected through hyperedge HE-3 (induced by source paper "upper bounds via lamination on the constrained secrecy capacity of hypergraphical sources"):
  with members:
    - "multiterminal secret key agreement at asymptotically zero discussion rate"
    - "secret key agreement under discussion rate constraints"
    - "on the optimality of secret key agreement via omniscience"
    - "bounds on the communication rate needed to achieve sk capacity in the hypergraphical source model"
    - "secret key generation with limited interaction"
    - "on the public communication needed to achieve sk capacity in the multiterminal source model"
    - "coded cooperative data exchange for a secret key"
    - "common information and secret key capacity"

Connected through hyperedge HE-4 (induced by source paper "compressed secret key agreement maximizing multivariate mutual information per bit"):
  with members:
    - "secret key agreement under discussion rate constraints"
    - "opening the black box of deep neural networks via information"
    - "on the optimality of secret key agreement via omniscience"
    - "bounds on the communication rate needed to achieve sk capacity in the hypergraphical source model"
    - "duality between feature selection and data clustering"
    - "a lattice coding scheme for secret key generation from gaussian markov tree sources"
    - "common randomness and key generation with limited interaction"
    - "info clustering a mathematical theory for data clustering"

Connected through hyperedge HE-5 (induced by source paper "on the optimality of secret key agreement via omniscience"):
  with members:
    - "secret key agreement under discussion rate constraints"
    - "compressed secret key agreement maximizing multivariate mutual information per bit"
    - "bounds on the communication rate needed to achieve sk capacity in the hypergraphical source model"
    - "duality between feature selection and data clustering"
    - "info clustering a mathematical theory for data clustering"
    - "on the public communication needed to achieve sk capacity in the multiterminal source model"
    - "the communication complexity of achieving sk capacity in a class of pin models"
    - "achieving sk capacity in the source model when must all terminals talk"

Connected through hyperedge HE-6 (induced by source paper "secret key agreement under discussion rate constraints"):
  with members:
    - "bounds on the communication rate needed to achieve sk capacity in the hypergraphical source model"
    - "common randomness and key generation with limited interaction"
    - "on the public communication needed to achieve sk capacity in the multiterminal source model"
    - "achieving sk capacity in the source model when must all terminals talk"
    - "common information and secret key capacity"
    - "perfect omniscience perfect secrecy and steiner tree packing"
    - "secret key generation for a pairwise independent network model"

Connected through hyperedge HE-7 (induced by source paper "info clustering a mathematical theory for data clustering"):
  with members:
    - "bounds on the communication rate needed to achieve sk capacity in the hypergraphical source model"
    - "duality between feature selection and data clustering"
    - "fairness in communication for omniscience"
    - "on the public communication needed to achieve sk capacity in the multiterminal source model"
    - "iterative merging algorithm for cooperative data exchange"
    - "deep residual learning for image recognition"
    - "the communication complexity of achieving sk capacity in a class of pin models"
    - "parallel correlation clustering on big graphs"

Connected through hyperedge HE-8 (induced by source paper "bounds on the communication rate needed to achieve sk capacity in the hypergraphical source model"):
  with members:
    - "on the public communication needed to achieve sk capacity in the multiterminal source model"
    - "the communication complexity of achieving sk capacity in a class of pin models"
    - "coded cooperative data exchange for a secret key"
    - "on the communication complexity of secret key generation in the multiterminal source model"
    - "wyner s common information generalizations and a new lossy source coding interpretation"
    - "common information and secret key capacity"
    - "coded cooperative data exchange in multihop networks"
    - "perfect omniscience perfect secrecy and steiner tree packing"

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)