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: "potent tree codes and their applications coding for interactive communication revisited"
  Abstract: We study the fundamental problem of reliable interactive communication over a noisy channel. In a breakthrough sequence of papers published in 1992 and 1993, Schulman gave non-constructive proofs of the existence of general methods to emulate any two-party interactive protocol such that: (1) the emulation protocol takes a constant-factor longer than the original protocol, and (2) if the emulation protocol is executed over a noisy channel, then the probability that the emulation protocol fails is exponentially small in the total length of the protocol. Unfortunately, Schulman's emulation procedures either only work in a model with a large amount of shared randomness, or are non-constructive in that they rely on the existence of good tree codes. The only known proofs of the existence of good tree codes are non-constructive, and finding an explicit construction remains an important open problem. Indeed, randomly generated tree codes are not good tree codes with overwhelming probability. #R##N#In this work, we revisit the problem of reliable interactive communication, and obtain the following results: We introduce a new notion of goodness for a tree code, and define the notion of a potent tree code. We believe that this notion is of independent interest. We prove the correctness of an explicit emulation procedure based on any potent tree code. We show that a randomly generated tree code (with suitable constant alphabet size) is a potent tree code with overwhelming probability. Furthermore we are able to partially derandomize this result using only O(n) random bits, where $n$ is the depth of the tree. #R##N#These results allow us to obtain the first fully explicit emulation procedure for reliable interactive communication over noisy channels with a constant communication overhead, and exponentially small failure probability.

Connected through hyperedge HE-1 (induced by source paper "robust causal transform coding for lqg systems with delay loss in communications"):
  with members:
    - "error correcting codes for distributed control"

Connected through hyperedge HE-2 (induced by source paper "error correcting codes for distributed control"):
  with members:
    - "capacity achieving random sparse linear codes"

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.DS(Data Structures and Algorithms)