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: "tight information theoretic converse results for some pliable index coding problems"
  Abstract: This paper studies the Pliable Index CODing problem (PICOD), which models content-type distribution networks. In the PICOD$(t)$ problem there are $m$ messages, $n$ users and each user has a distinct message side information set, as in the classical Index Coding problem (IC). Differently from IC, where each user has a pre-specified set of messages to decode, in the PICOD$(t)$ a user is "pliable" and is satisfied if it can decode any $t$ messages that are not in its side information set. The goal is to find a code with the shortest length that satisfies all the users. This flexibility in determining the desired message sets makes the PICOD$(t)$ behave quite differently compared to the IC, and its analysis challenging. #R##N#This paper mainly focuses on the \emph{complete--$S$} PICOD$(t)$ with $m$ messages, where the set $S\subset[m]$ contains the sizes of the side information sets, and the number of users is $n=\sum_{s\in S}\binom{m}{s}$, with no two users having the same side information set. Capacity results are shown for: (i) the \emph{consecutive} complete--$S$ PICOD$(t)$, where $S=[s_{\min}:s_{\max}]$ for some $0 \leq s_{\min} \leq s_{\max} \leq m-t$, and (ii) the \emph{complement-consecutive} complete--$S$ PICOD$(t)$, where $S=[0:m-t]\backslash[s_{\min}:s_{\max}]$, for some $0 < s_{\min} \leq s_{\max} < m-t$. The novel converse proof is inspired by combinatorial design techniques and the key insight is to consider all messages that a user can eventually decode successfully, even those in excess of the $t$ required ones. This allows one to circumvent the need to consider all possible desired message set assignments at the users in order to find the one that leads to the shortest code length. #R##N#In addition, tight converse results are also shown for those PICOD$(1)$ with circular-arc network topology hypergraph.

Connected through hyperedge HE-1 (induced by source paper "secure decentralized pliable index coding"):
  with members:
    - "task based solutions to embedded index coding"
    - "embedded index coding"
    - "private pliable index coding"
    - "on pliable index coding"
    - "improved lower bounds for pliable index coding using absent receivers"
    - "decentralized pliable index coding"
    - "optimal rate characterisation for pliable index coding using absent receivers"
    - "capacity theorems for distributed index coding"

Connected through hyperedge HE-2 (induced by source paper "decentralized pliable index coding"):
  with members:
    - "mds matrices over small fields a proof of the gm mds conjecture"
    - "capacity theorems for distributed index coding"
    - "the benefit of being flexible in distributed computation"
    - "the single uniprior index coding problem the single sender case and the multi sender extension"
    - "a polynomial time algorithm for pliable index coding"
    - "efficient algorithms for the data exchange problem"
    - "fundamental limits of caching in wireless d2d networks"
    - "coded cooperative data exchange in multihop networks"

Connected through hyperedge HE-3 (induced by source paper "private pliable index coding"):
  with members:
    - "on pliable index coding"
    - "private broadcasting an index coding approach"
    - "a polynomial time algorithm for pliable index coding"
    - "the capacity of private information retrieval"
    - "content type coding"
    - "topological interference management through index coding"
    - "on the security of index coding with side information"

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)