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: "context aware proactive content caching with service differentiation in wireless networks"
  Abstract: Content caching in small base stations or wireless infostations is considered to be a suitable approach to improve the efficiency in wireless content delivery. Placing the optimal content into local caches is crucial due to storage limitations, but it requires knowledge about the content popularity distribution, which is often not available in advance. Moreover, local content popularity is subject to fluctuations, since mobile users with different interests connect to the caching entity over time. Which content a user prefers may depend on the user’s context. In this paper, we propose a novel algorithm for context-aware proactive caching. The algorithm learns context-specific content popularity online by regularly observing context information of connected users, updating the cache content and observing cache hits subsequently. We derive a sublinear regret bound, which characterizes the learning speed and proves that our algorithm converges to the optimal cache content placement strategy in terms of maximizing the number of cache hits. Furthermore, our algorithm supports service differentiation by allowing operators of caching entities to prioritize customer groups. Our numerical results confirm that our algorithm outperforms state-of-the-art algorithms in a real world data set, with an increase in the number of cache hits of at least 14%.

Connected through hyperedge HE-1 (induced by source paper "aoi delay tradeoff in mobile edge caching with freshness aware content refreshing"):
  with members:
    - "cooperative service caching and workload scheduling in mobile edge computing"
    - "ai assisted low information latency wireless networking"
    - "age of information aware radio resource management in vehicular networks a proactive deep reinforcement learning perspective"
    - "minimum age of information in the internet of things with non uniform status packet sizes"
    - "content popularity prediction towards location aware mobile edge caching"
    - "air ground integrated vehicular network slicing with content pushing and caching"
    - "cost effective cache deployment in mobile heterogeneous networks"
    - "edge caching wireless networks performance analysis and optimization"

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"
    - "caching placement in stochastic wireless caching helper networks channel selection diversity via caching"
    - "placing dynamic content in caches with small population"
    - "optimal geographic caching in cellular networks"

Connected through hyperedge HE-3 (induced by source paper "viewport aware deep reinforcement learning approach for 360 o video caching"):
  with members:
    - "applications of deep reinforcement learning in communications and networking a survey"
    - "cost effective cache deployment in mobile heterogeneous networks"
    - "saltinet scan path prediction on 360 degree images using saliency volumes"
    - "edge caching wireless networks performance analysis and optimization"
    - "deep reinforcement learning framework applications and embedded implementations"
    - "a deep reinforcement learning based framework for content caching"
    - "caching at the wireless edge design aspects challenges and future directions"
    - "deep reinforcement learning in large discrete action spaces"

Connected through hyperedge HE-4 (induced by source paper "optimal pricing of internet of things a machine learning approach"):
  with members:
    - "hybrid pricing for mobile collaborative internet access"
    - "a reinforcement learning approach to proactive caching in wireless networks"
    - "scalable mobile crowdsensing via peer to peer data sharing"
    - "mobile big data analytics using deep learning and apache spark"
    - "context aware computing for the internet of things a survey"
    - "machine learning in wireless sensor networks algorithms strategies and applications"
    - "a theory of pricing private data"
    - "a survey of smart data pricing past proposals current plans and future trends"

Connected through hyperedge HE-5 (induced by source paper "mobility aware content preference learning in decentralized caching networks"):
  with members:
    - "decentralized multi task learning based on extreme learning machines"
    - "user preference learning based edge caching for fog radio access network"
    - "exploiting mobility in cache assisted d2d networks performance analysis and optimization"
    - "learning to reweight examples for robust deep learning"
    - "mobility and popularity aware coded small cell caching"
    - "caching policy for cache enabled d2d communications by learning user preference"
    - "optimizing content caching to maximize the density of successful receptions in device to device networking"
    - "effect of user mobility on the performance of device to device networks with distributed caching"

Connected through hyperedge HE-6 (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"
    - "caching with time varying popularity profiles a learning theoretic perspective"
    - "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"

Connected through hyperedge HE-7 (induced by source paper "edge computing in the dark leveraging contextual combinatorial bandit and coded computing"):
  with members:
    - "timely throughput optimal coded computing over cloud networks"
    - "combinatorial sleeping bandits with fairness constraints"
    - "hierarchical coded computation"
    - "speeding up distributed machine learning using codes"
    - "differentially private contextual linear bandits"
    - "communication aware scheduling of serial tasks for dispersed computing"
    - "lagrange coded computing optimal design for resiliency security and privacy"
    - "coded computation over heterogeneous clusters"

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

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.NI(Networking and Internet Architecture)