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: "caching with time varying popularity profiles a learning theoretic perspective"
  Abstract: Content caching at the small-cell base stations (sBSs) in a heterogeneous wireless network is considered. A cost function is proposed that captures the backhaul link load called the `offloading loss', which measures the fraction of the requested files that are not available in the sBS caches. As opposed to the previous approaches that consider time-invariant and perfectly known popularity profile, caching with non-stationary and statistically dependent popularity profiles (assumed unknown, and hence, estimated) is studied from a learning-theoretic perspective. A probably approximately correct result is derived, which presents a high probability bound on the offloading loss difference, i.e., the error between the estimated and the optimal offloading loss. The difference is a function of the Rademacher complexity, the $\beta-$mixing coefficient, the number of time slots, and a measure of discrepancy between the estimated and true popularity profiles. A cache update algorithm is proposed, and simulation results are presented to show its superiority over periodic updates. The performance analyses for Bernoulli and Poisson request models are also presented.

Connected through hyperedge HE-1 (induced by source paper "optimal scheduling of content caching subject to deadline"):
  with members:
    - "on optimal proactive and retention aware caching with user mobility"
    - "caching at base stations with heterogeneous user demands and spatial locality"
    - "a rolling horizon dynamic programming approach for collaborative caching"
    - "accounting for information freshness in scheduling of content caching"
    - "using grouped linear prediction and accelerated reinforcement learning for online content caching"
    - "optimal geographic caching in cellular networks with linear content coding"
    - "cost optimal caching for d2d networks with user mobility modeling analysis and computational approaches"
    - "a learning based approach to caching in heterogenous small cell networks"

Connected through hyperedge HE-2 (induced by source paper "the study of dynamic caching via state transition field the case of time invariant popularity"):
  with members:
    - "content popularity prediction towards location aware mobile edge caching"
    - "using grouped linear prediction and accelerated reinforcement learning for online content caching"
    - "optimal and scalable caching for 5g using reinforcement learning of space time popularities"
    - "enabling edge cooperation in tactile internet via 3c resource sharing"
    - "air ground integrated vehicular network slicing with content pushing and caching"
    - "a reinforcement learning approach to proactive caching in wireless networks"
    - "online edge caching and wireless delivery in fog aided networks with dynamic content popularity"
    - "context aware proactive content caching with service differentiation in wireless networks"

Connected through hyperedge HE-3 (induced by source paper "a rolling horizon dynamic programming approach for collaborative caching"):
  with members:
    - "popnetcod a popularity based caching policy for network coding enabled named data networking"
    - "content popularity prediction towards location aware mobile edge caching"
    - "using grouped linear prediction and accelerated reinforcement learning for online content caching"
    - "optimal and scalable caching for 5g using reinforcement learning of space time popularities"
    - "context aware proactive content caching with service differentiation in wireless networks"
    - "wireless content caching for small cell and d2d networks"
    - "joint caching routing and channel assignment for collaborative small cell cellular networks"
    - "adaptive prioritized random linear coding and scheduling for layered data delivery from multiple servers"

Connected through hyperedge HE-4 (induced by source paper "accounting for information freshness in scheduling of content caching"):
  with members:
    - "dynamic content updates in heterogeneous wireless networks"
    - "age of information aware cache updating with file and age dependent update durations"
    - "on optimal proactive and retention aware caching with user mobility"
    - "using grouped linear prediction and accelerated reinforcement learning for online content caching"
    - "optimal geographic caching in cellular networks with linear content coding"
    - "cost optimal caching for d2d networks with user mobility modeling analysis and computational approaches"
    - "update or wait how to keep your data fresh"
    - "capacity of cellular networks with femtocache"

Connected through hyperedge HE-5 (induced by source paper "dynamic content updates in heterogeneous wireless networks"):
  with members:
    - "content popularity prediction towards location aware mobile edge caching"
    - "using grouped linear prediction and accelerated reinforcement learning for online content caching"
    - "optimal and scalable caching for 5g using reinforcement learning of space time popularities"
    - "mobility and popularity aware coded small cell caching"
    - "understanding performance of edge content caching for mobile video streaming"
    - "context aware proactive content caching with service differentiation in wireless networks"
    - "learning based optimization of cache content in a small cell base station"

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)