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: "mmse of bad codes"
  Abstract: We examine codes, over the additive Gaussian noise channel, designed for reliable communication at some specific signal-to-noise ratio (SNR) and constrained by the permitted minimum mean-square error (MMSE) at lower SNRs. The maximum possible rate is below point-to-point capacity, and hence these are non-optimal codes (alternatively referred to as "bad" codes). We show that the maximum possible rate is the one attained by superposition codebooks. Moreover, the MMSE and mutual information behavior as a function of SNR, for any code attaining the maximum rate under the MMSE constraint, is known for all SNR. We also provide a lower bound on the MMSE for finite length codes, as a function of the error probability of the code.

Connected through hyperedge HE-1 (induced by source paper "on communication through a gaussian channel with an mmse disturbance constraint"):
  with members:
    - "interference as noise friend or foe"
    - "on the two user interference channel with lack of knowledge of the interference codebook at one receiver"
    - "soft decoding based strategies for relay and interference channels analysis and achievable rates using ldpc codes"
    - "analysis of mismatched estimation errors using gradients of partition functions"
    - "statistical physics of signal estimation in gaussian noise theory and examples of phase transitions"
    - "estimation in gaussian noise properties of the minimum mean square error"
    - "a new outer bound and the noisy interference sum rate capacity for gaussian interference channels"
    - "capacity bounds for the gaussian interference channel"

Connected through hyperedge HE-2 (induced by source paper "on the minimum mean p th error in gaussian noise channels and its applications"):
  with members:
    - "on communication through a gaussian channel with an mmse disturbance constraint"
    - "lower bounds on parameter modulation estimation under bandwidth constraints"
    - "interference as noise friend or foe"
    - "exponential error bounds on parameter modulation estimation for discrete memoryless channels"
    - "on conditions for linearity of optimal estimation"
    - "statistical physics of signal estimation in gaussian noise theory and examples of phase transitions"
    - "estimation in gaussian noise properties of the minimum mean square error"
    - "mutual information and minimum mean square error in gaussian channels"

Connected through hyperedge HE-3 (induced by source paper "on mmse properties of codes for the gaussian broadcast and wiretap channels"):
  with members:
    - "polar coding for the broadcast channel with confidential messages and constrained randomization"
    - "polynomial time semantically secure encryption achieving the secrecy capacity"
    - "statistical physics of signal estimation in gaussian noise theory and examples of phase transitions"
    - "estimation in gaussian noise properties of the minimum mean square error"
    - "construction of wiretap codes from ordinary channel codes"
    - "the secrecy capacity of the mimo wiretap channel"
    - "mutual information and minimum mean square error in gaussian channels"

Connected through hyperedge HE-4 (induced by source paper "the effect of maximal rate codes on the interfering message rate"):
  with members:
    - "on mmse properties of codes for the gaussian broadcast and wiretap channels"
    - "sub optimality of the han kobayashi achievable region for interference channels"
    - "random coding error exponents for the two user interference channel"
    - "wasserstein continuity of entropy and outer bounds for interference channels"
    - "on the two user interference channel with lack of knowledge of the interference codebook at one receiver"
    - "sub optimality of treating interference as noise in the cellular uplink with weak interference"
    - "on discrete alphabets for the two user gaussian interference channel with one receiver lacking knowledge of the interfering codebook"
    - "on the optimality of treating interference as noise general message sets"

Connected through hyperedge HE-5 (induced by source paper "soft decoding based strategies for relay and interference channels analysis and achievable rates using ldpc codes"):
  with members:
    - "on the performance of low density parity check codes for gaussian interference channels"
    - "statistical physics of signal estimation in gaussian noise theory and examples of phase transitions"
    - "a theory of network equivalence parts i and ii"
    - "compute and forward harnessing interference through structured codes"
    - "joint physical layer coding and network coding for bi directional relaying"
    - "gaussian interference channel capacity to within one bit"
    - "network coding over a noisy relay a belief propagation approach"
    - "the generalized area theorem and some of its consequences"

Connected through hyperedge HE-6 (induced by source paper "analysis of mismatched estimation errors using gradients of partition functions"):
  with members:
    - "optimum estimation via gradients of partition functions and information measures a statistical mechanical perspective"
    - "accurate prediction of phase transitions in compressed sensing via a connection to minimax denoising"
    - "statistical physics of signal estimation in gaussian noise theory and examples of phase transitions"
    - "on regret of parametric mismatch in minimum mean square error estimation"
    - "mutual information relative entropy and estimation in the poisson channel"
    - "message passing algorithms for compressed sensing"
    - "universal minimax discrete denoising under channel uncertainty"
    - "mutual information and minimum mean square error in gaussian 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)