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: "distributive stochastic learning for delay optimal ofdma power and subband allocation"
  Abstract: In this paper, we consider the distributive queue-aware power and subband allocation design for a delay-optimal OFDMA uplink system with one base station, K users and NF independent subbands. Each mobile has an uplink queue with heterogeneous packet arrivals and delay requirements. We model the problem as an infinite horizon average reward Markov decision problem (MDP) where the control actions are functions of the instantaneous channel state information (CSI) as well as the joint queue state information (QSI). To address the distributive requirement and the issue of exponential memory requirement and computational complexity, we approximate the subband allocation Q-factor by the sum of the per-user subband allocation Q-factor and derive a distributive online stochastic learning algorithm to estimate the per-user Q-factor and the Lagrange multipliers (LM) simultaneously and determine the control actions using an auction mechanism. We show that under the proposed auction mechanism, the distributive online learning converges almost surely (with probability 1). For illustration, we apply the proposed distributive stochastic learning framework to an application example with exponential packet size distribution. We show that the delay-optimal power control has the multilevel water-filling structure where the CSI determines the instantaneous power allocation and the QSI determines the water-level. The proposed algorithm has linear signaling overhead and computational complexity O(KNF), which is desirable from an implementation perspective.

Connected through hyperedge HE-1 (induced by source paper "joint optimization of file placement and delivery in cache assisted wireless networks with limited lifetime and cache space"):
  with members:
    - "joint downlink scheduling for file placement and delivery in cache assisted wireless networks with finite file lifetime"
    - "optimal caching designs for perfect imperfect and unknown file popularity distributions in large scale multi tier wireless networks"
    - "online user scheduling and resource allocation for mobile edge computing systems"
    - "cooperative job dispatching in edge computing network with unpredictable uploading delay"
    - "mdp based scheduling design for mobile edge computing systems with random user arrival"
    - "modeling analysis and optimization of coded caching in small cell networks"
    - "stochastic content centric multicast scheduling for cache enabled heterogeneous cellular networks"
    - "wireless device to device caching networks basic principles and system performance"

Connected through hyperedge HE-2 (induced by source paper "deep learning based wireless resource allocation with application to vehicular networks"):
  with members:
    - "learning to branch accelerating resource allocation in wireless networks"
    - "spectrum sharing in vehicular networks based on multi agent reinforcement learning"
    - "learning to detect"
    - "learning optimal resource allocations in wireless systems"
    - "deep learning based end to end wireless communication systems with conditional gan as unknown channel"
    - "distributed power control for large energy harvesting networks a multi agent deep reinforcement learning approach"
    - "power allocation in multi user cellular networks deep reinforcement learning approaches"
    - "toward intelligent vehicular networks a machine learning framework"

Connected through hyperedge HE-3 (induced by source paper "whittle index policy for multichannel scheduling in queueing systems"):
  with members:
    - "asymptotically optimal delay aware scheduling in wireless networks"
    - "a survey on delay aware resource control for wireless systems large deviation theory stochastic lyapunov drift and distributed stochastic learning"

Connected through hyperedge HE-4 (induced by source paper "joint status sampling and updating for minimizing age of information in the internet of things"):
  with members:
    - "scheduling policies for minimizing age of information in broadcast wireless networks"
    - "can decentralized status update achieve universally near optimal age of information in wireless multiaccess channels"
    - "timely status update in massive iot systems decentralized scheduling for wireless uplinks"
    - "age optimal sampling and transmission scheduling in multi source systems"
    - "scheduling status updates to minimize age of information with an energy harvesting sensor"
    - "optimal status update for age of information minimization with an energy harvesting source"
    - "average age of information with hybrid arq under a resource constraint"
    - "artificial neural networks based machine learning for wireless networks a tutorial"

Connected through hyperedge HE-5 (induced by source paper "joint content delivery and caching placement via dynamic programming"):
  with members:
    - "modeling analysis and optimization of coded caching in small cell networks"
    - "wireless device to device caching networks basic principles and system performance"
    - "analysis and optimization of caching and multicasting in large scale cache enabled heterogeneous wireless networks"
    - "caching placement in stochastic wireless caching helper networks channel selection diversity via caching"
    - "analysis on cache enabled wireless heterogeneous networks"
    - "optimal dynamic multicast scheduling for cache enabled content centric wireless networks"
    - "cache enabled small cell networks modeling and tradeoffs"
    - "mixed timescale precoding and cache control in cached mimo interference network"

Connected through hyperedge HE-6 (induced by source paper "delay aware uplink fronthaul allocation in cloud radio access networks"):
  with members:
    - "dynamic power control for delay aware device to device communications"
    - "full duplex cloud radio access networks an information theoretic viewpoint"
    - "optimized backhaul compression for uplink cloud radio access network"
    - "joint power control and fronthaul rate allocation for throughput maximization in ofdma based cloud radio access network"
    - "joint precoding and multivariate backhaul compression for the downlink of cloud radio access networks"
    - "multihop backhaul compression for the uplink of cloud radio access networks"
    - "a survey on delay aware resource control for wireless systems large deviation theory stochastic lyapunov drift and distributed stochastic learning"
    - "queue aware dynamic clustering and power allocation for network mimo systems via distributed stochastic learning"

Connected through hyperedge HE-7 (induced by source paper "delay aware bs discontinuous transmission control and user scheduling for energy harvesting downlink coordinated mimo systems"):
  with members:
    - "solving pomdps by searching the space of finite policies"
    - "multi antenna communication in ad hoc networks achieving mimo gains with simo transmission"
    - "a tractable approach to coverage and rate in cellular networks"
    - "networked mimo with clustered linear precoding"

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.LG(Machine Learning)