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: "learning based optimization of cache content in a small cell base station"
  Abstract: Optimal cache content placement in a wireless small cell base station (sBS) with limited backhaul capacity is studied. The sBS has a large cache memory and provides content-level selective offloading by delivering high data rate contents to users in its coverage area. The goal of the sBS content controller (CC) is to store the most popular contents in the sBS cache memory such that the maximum amount of data can be fetched directly form the sBS, not relying on the limited backhaul resources during peak traffic periods. If the popularity profile is known in advance, the problem reduces to a knapsack problem. However, it is assumed in this work that, the popularity profile of the files is not known by the CC, and it can only observe the instantaneous demand for the cached content. Hence, the cache content placement is optimised based on the demand history. By refreshing the cache content at regular time intervals, the CC tries to learn the popularity profile, while exploiting the limited cache capacity in the best way possible. Three algorithms are studied for this cache content placement problem, leading to different exploitation-exploration trade-offs. We provide extensive numerical simulations in order to study the time-evolution of these algorithms, and the impact of the system parameters, such as the number of files, the number of users, the cache size, and the skewness of the popularity profile, on the performance. It is shown that the proposed algorithms quickly learn the popularity profile for a wide range of system parameters.

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"
    - "caching with time varying popularity profiles a learning theoretic perspective"
    - "optimal geographic caching in cellular networks with linear content coding"
    - "cost optimal caching for d2d networks with user mobility modeling analysis and computational approaches"

Connected through hyperedge HE-2 (induced by source paper "collaborative multi agent multi armed bandit learning for small cell caching"):
  with members:
    - "content popularity prediction towards location aware mobile edge caching"
    - "optimal and scalable caching for 5g using reinforcement learning of space time popularities"
    - "modeling analysis and optimization of coded caching in small cell networks"
    - "a deep reinforcement learning based framework for content caching"
    - "caching policy for cache enabled d2d communications by learning user preference"
    - "context aware proactive content caching with service differentiation in wireless networks"
    - "caching placement in stochastic wireless caching helper networks channel selection diversity via caching"
    - "placing dynamic content in caches with small population"

Connected through hyperedge HE-3 (induced by source paper "a personalized preference learning framework for caching in mobile networks"):
  with members:
    - "caching at base stations with heterogeneous user demands and spatial locality"
    - "user preference learning based edge caching for fog radio access network"
    - "on the effects of subpacketization in content centric mobile networks"
    - "how to cache in mobile hybrid iot networks"
    - "caching policy for cache enabled d2d communications by learning user preference"
    - "pricing and resource allocation via game theory for a small cell video caching system"
    - "information theoretic caching the multi user case"
    - "caching incentive design in wireless d2d networks a stackelberg game approach"

Connected through hyperedge HE-4 (induced by source paper "optimal caching designs for perfect imperfect and unknown file popularity distributions in large scale multi tier wireless networks"):
  with members:
    - "optimal and scalable caching for 5g using reinforcement learning of space time popularities"
    - "random caching based cooperative transmission in heterogeneous wireless networks"
    - "a deep reinforcement learning based framework for content caching"
    - "caching policy for cache enabled d2d communications by learning user preference"
    - "a learning based approach to caching in heterogenous small cell networks"
    - "optimization and analysis of probabilistic caching in n tier heterogeneous networks"
    - "analysis and optimization of caching and multicasting in large scale cache enabled heterogeneous wireless networks"
    - "cooperative caching and transmission design in cluster centric small cell networks"

Connected through hyperedge HE-5 (induced by source paper "deep reinforcement learning for adaptive caching in hierarchical content delivery networks"):
  with members:
    - "joint switch upgrade and controller deployment in hybrid software defined networks"
    - "bandit online learning with unknown delays"
    - "optimal and scalable caching for 5g using reinforcement learning of space time popularities"
    - "applications of deep reinforcement learning in communications and networking a survey"
    - "deep reinforcement learning based mode selection and resource management for green fog radio access networks"
    - "decentralized caching for content delivery based on blockchain a game theoretic perspective"
    - "a reinforcement learning approach to proactive caching in wireless networks"
    - "deep reinforcement learning a brief survey"

Connected through hyperedge HE-6 (induced by source paper "distributed edge caching via reinforcement learning in fog radio access networks"):
  with members:
    - "user preference learning based edge caching for fog radio access network"
    - "optimal and scalable caching for 5g using reinforcement learning of space time popularities"
    - "distributed edge caching in ultra dense fog radio access networks a mean field approach"
    - "ultra dense edge caching under spatio temporal demand and network dynamics"
    - "offloading content with self organizing mobile fogs"
    - "a cmdp based approach for energy efficient power allocation in massive mimo systems"
    - "context aware proactive content caching with service differentiation in wireless networks"
    - "fog computing based radio access networks issues and challenges"

Connected through hyperedge HE-7 (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"
    - "caching with time varying popularity profiles a learning theoretic perspective"
    - "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"

Connected through hyperedge HE-8 (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"
    - "caching with time varying popularity profiles a learning theoretic perspective"
    - "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"

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)