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: "dynamic asymmetric communication"
  Abstract: Summary form only given. Internet users usually download more than they upload and many technologies have asymmetric bandwidth. Suppose some clients want to send messages to a server. At any point, the server knows all the messages it has received so far; each client only knows its own message or messages and does not overhear communication between other clients and the server. Thus, the server may be able to compress the messages but the clients individually cannot. By assuming the server, after receiving a sample of messages, can accurately estimate the distribution of all the messages, a multi-round asymmetric communication protocol can be provided in which the server uses its greater bandwidth to help a single client send a message drawn from a distribution known to the server. The server can just repeat their protocol to help any number of clients, provided it starts with a representative sample. This paper propose a new protocol inspired by an everyday act: placing a call on a cell phone. While the protocol needs no assumptions and is nearly optimal with respect to the number of bits the clients send, the server sends a relatively large number of bits, which is necessary in order to use only one round of communication for each message.

Connected through hyperedge HE-1 (induced by source paper "efficient and compact representations of prefix codes"):
  with members:
    - "new lower and upper bounds for representing sequences"
    - "on compressing permutations and adaptive sorting"
    - "fixed block compression boosting in fm indexes"
    - "compressed representations of permutations and applications"
    - "fast and compact prefix codes"
    - "worst case optimal adaptive prefix coding"
    - "large alphabets and incompressibility"
    - "time space trade offs for predecessor search"

Connected through hyperedge HE-2 (induced by source paper "new algorithms and lower bounds for sequential access data compression"):
  with members:
    - "on optimally partitioning a text to improve its compression"
    - "low memory adaptive prefix coding"
    - "reversal complexity revisited"
    - "large alphabets and incompressibility"
    - "tight lower bounds for query processing on streaming and external memory data"
    - "dynamic shannon coding"

Connected through hyperedge HE-3 (induced by source paper "fast and compact prefix codes"):
  with members:
    - "worst case optimal adaptive prefix coding"
    - "large alphabets and incompressibility"

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)