human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "algorithms with logarithmic or sublinear regret for constrained contextual bandits"):
  Abstract: We study contextual bandits with budget and time constraints, referred to as constrained contextual bandits.The time and budget constraints significantly complicate the exploration and exploitation tradeoff because they introduce complex coupling among contexts over time.Such coupling effects make it difficult to obtain oracle solutions that assume known statistics of bandits. To gain insight, we first study unit-cost systems with known context distribution. When the expected rewards are known, we develop an approximation of the oracle, referred to Adaptive-Linear-Programming (ALP), which achieves near-optimality and only requires the ordering of expected rewards. With these highly desirable features, we then combine ALP with the upper-confidence-bound (UCB) method in the general case where the expected rewards are unknown {\it a priori}. We show that the proposed UCB-ALP algorithm achieves logarithmic regret except for certain boundary cases. Further, we design algorithms and obtain similar regret analysis results for more general systems with unknown context distribution and heterogeneous costs. To the best of our knowledge, this is the first work that shows how to achieve logarithmic regret in constrained contextual bandits. Moreover, this work also sheds light on the study of computationally efficient algorithms for general constrained contextual bandits.

Includes members:
  Member "thompson sampling for budgeted multi armed bandits":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "online joint bid daily budget optimization of internet advertising campaigns")
  Member "contextual bandits with global constraints and objective":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "matching while learning")
  Member "a survey on contextual multi armed bandits":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "adaptive metamorphic testing with contextual bandits")
  Member "linear contextual bandits with global constraints and objective":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "matching while learning")
  Member "bandits with concave rewards and convex knapsacks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "exploration exploitation in constrained mdps")
  Member "resourceful contextual bandits":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "advances in bandits with knapsacks")
  Member "taming the monster a fast and simple algorithm for contextual bandits":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "neural contextual bandits with ucb based exploration")
  Member "bandits with knapsacks":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "exploration exploitation in constrained mdps")

Question: Please tell me which class the source paper 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)