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: "adaptive caching networks with optimality guarantees"
  Abstract: We study the problem of optimal content placement over a network of caches, a problem naturally arising in several networking applications, including ICNs, CDNs, and P2P systems. Given a demand of content request rates and paths followed, we wish to determine the content placement that maximizes the expected caching gain, i.e., the reduction of routing costs due to intermediate caching. The offline version of this problem is NP-hard and, in general, the demand and topology may be a priori unknown. Hence, a distributed, adaptive, constant approximation content placement algorithm is desired. We show that path replication, a simple algorithm frequently encountered in literature, can be arbitrarily suboptimal when combined with traditional eviction policies, like LRU, LFU, or FIFO. We propose a distributed, adaptive algorithm that performs stochastic gradient ascent on a concave relaxation of the expected caching gain, and constructs a probabilistic content placement within 1-1/e factor from the optimal, in expectation. Motivated by our analysis, we also propose a novel greedy eviction policy to be used with path replication, and show through numerical evaluations that both algorithms significantly outperform path replication with traditional eviction policies over a broad array of network topologies.

Connected through hyperedge HE-1 (induced by source paper "a ttl based approach for content placement in edge networks"):
  with members:
    - "cache version selection and content placement for adaptive video streaming in wireless edge networks"
    - "jointly optimal routing and caching for arbitrary network topologies"
    - "a utility optimization approach to network cache design"
    - "on the complexity of optimal routing and content caching in heterogeneous networks"
    - "a unified approach to the performance analysis of caching systems"

Connected through hyperedge HE-2 (induced by source paper "cache optimization models and algorithms"):
  with members:
    - "learning to cache with no regrets"
    - "introduction to online convex optimization"
    - "cabaret leveraging recommendation systems for mobile edge caching"
    - "optimal and scalable caching for 5g using reinforcement learning of space time popularities"
    - "competitive caching with machine learned advice"
    - "online convex optimization and no regret learning algorithms guarantees and applications"
    - "show me the cache optimizing cache friendly recommendations for sequential content access"
    - "a reinforcement learning approach to proactive caching in wireless networks"

Connected through hyperedge HE-3 (induced by source paper "spatial soft core caching"):
  with members:
    - "the exact rate memory tradeoff for caching with uncoded prefetching"
    - "spatially correlated content caching for device to device communications"
    - "spatial multi lru caching for wireless networks with coverage overlaps"
    - "joint optimization of cloud and edge processing for fog radio access networks"
    - "optimal geographic caching in cellular networks"
    - "cache aided interference channels"
    - "fundamental limits of caching in wireless d2d networks"
    - "fundamental limits of caching"

Connected through hyperedge HE-4 (induced by source paper "a probabilistic approach for demand aware ride sharing optimization"):
  with members:
    - "deeppool distributed model free algorithm for ride sharing using deep reinforcement learning"
    - "movi a model free approach to dynamic fleet management"
    - "osmnx new methods for acquiring constructing analyzing and visualizing complex street networks"
    - "predictive positioning and quality of service ridesharing for campus mobility on demand systems"
    - "an optimization framework for online ride sharing markets"
    - "optimal geographic caching in cellular networks"

Connected through hyperedge HE-5 (induced by source paper "kelly cache networks"):
  with members:
    - "jointly optimal routing and caching for arbitrary network topologies"
    - "on the complexity of optimal routing and content caching in heterogeneous networks"
    - "vip a framework for joint dynamic forwarding and caching in named data networks"

Connected through hyperedge HE-6 (induced by source paper "reversing the meaning of node connectivity for content placement in networks of caches"):
  with members:
    - "jointly optimal routing and caching for arbitrary network topologies"
    - "maximizing coverage centrality via network design extended version"
    - "fundamental limits on throughput capacity in information centric networks"

Connected through hyperedge HE-7 (induced by source paper "updating content in cache aided coded multicast"):
  with members:
    - "centralized coded caching of correlated contents"
    - "coded multicast fronthauling and edge caching for multi connectivity transmission in fog radio access networks"
    - "communication cost for updating linear functions when message updates are sparse connections to maximally recoverable codes"
    - "cache aided coded multicast for correlated sources"
    - "coded caching with nonuniform demands"
    - "decentralized coded caching attains order optimal memory rate tradeoff"
    - "fundamental limits of caching"
    - "minimum cost multicast over coded packet networks"

Connected through hyperedge HE-8 (induced by source paper "joint data compression and caching approaching optimality with guarantees"):
  with members:
    - "jointly optimal routing and caching for arbitrary network topologies"
    - "what when and where to cache a unified optimization approach"
    - "network cache design under stationary requests exact analysis and poisson approximation"
    - "accurate learning or fast mixing dynamic adaptability of caching algorithms"
    - "on the complexity of optimal routing and content caching in heterogeneous 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.NI(Networking and Internet Architecture)