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Sequential learning for optimal monitoring of multi-channel wireless networks
15 references·1 citing·33 second hop
Sequential learning for optimal monitoring of multi-channel wireless networks (2011)Sequential learning for optimal monitorin…Combinatorial bandits (2012)Combinatorial banditsLinearly Parameterized Bandits (2010)Linearly Parameterized BanditsDecentralized multi-armed bandit with multiple distributed players (2010)Decentralized multi-armed ban…Exploration–exploitation tradeoff using variance estimates in multi-armed bandits (2009)Exploration–exploitation trad…Stochastic Linear Optimization Under Bandit Feedback (2008)Stochastic Linear Optimizatio…On Upper-Confidence Bound Policies for Non-Stationary Bandit Problems (2008)On Upper-Confidence Bound Pol…Tuning Bandit Algorithms in Stochastic Environments (2007)Tuning Bandit Algorithms in S…Regret Minimization Under Partial Monitoring (2006)Regret Minimization Under Par…Using upper confidence bounds for online learning (2002)Using upper confidence bounds…Gambling in a rigged casino: The adversarial multi-armed bandit problem (2002)Gambling in a rigged casino: …Finite-time Analysis of the Multiarmed Bandit Problem (2002)Finite-time Analysis of the M…Sample mean based index policies byO(logn) regret for the multi-armed bandit problem (1995)Sample mean based index polic…Asymptotically efficient adaptive allocation rules for the multiarmed bandit problem with switching cost (1988)Asymptotically efficient adap…Asymptotically efficient allocation rules for the multiarmed bandit problem with multiple plays-Part I: I.I.D. rewards (1987)Asymptotically efficient allo…Some aspects of the sequential design of experiments (1952)Some aspects of the sequentia…1Joint Channel Selection and Power Control in Infrastructureless Wireless Networks: A Multi-Player Multi-Armed Bandit Framework (2016)1Joint Channel Selection and …A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting (1997)Prediction, Learning, and Games (2006)Unimodal Bandits: Regret Lower Bounds and Optimal Algorithms (2014)A Survey of Online Experiment Design with the Stochastic Multi-Armed Bandit (2015)A Change-Detection Based Framework for Piecewise-Stationary Multi-Armed Bandit Problem (2018)A Stochastic Approximation Method (1951)Bandit Processes and Dynamic Allocation Indices (1979)Information-Theoretic Regret Bounds for Gaussian Process Optimization in the Bandit Setting (2012)Multi-Armed Bandit Allocation Indices. (1990)The KL-UCB Algorithm for Bounded Stochastic Bandits and Beyond (2011)Thompson Sampling: An Asymptotically Optimal Finite-Time Analysis (2012)Intrinsic motivation, curiosity, and learning (2016)The Nonstochastic Multiarmed Bandit Problem (2002)Efficient algorithms for online decision problems (2004)From Bandits to Experts: On the Value of Side-Observations (2011)Regret in Online Combinatorial Optimization (2013)Tight Regret Bounds for Stochastic Combinatorial Semi-Bandits (2014)Using confidence bounds for exploitation-exploration trade-offs (2003)Contextual Bandits with Linear Payoff Functions (2011)Thompson Sampling for Contextual Bandits with Linear Payoffs (2012)Learning to Optimize via Posterior Sampling (2014)On Upper-Confidence Bound Policies for Switching Bandit Problems (2011)Unbiased offline evaluation of contextual-bandit-based news article recommendation algorithms (2011)Combinatorial Network Optimization With Unknown Variables: Multi-Armed Bandits With Linear Rewards and Individual Observations (2012)An Information-Theoretic Analysis of Thompson Sampling (2014)A Tutorial on Thompson Sampling (2018)The Continuum-Armed Bandit Problem (1995)Indexability of Restless Bandit Problems and Optimality of Whittle Index for Dynamic Multichannel Access (2010)Combinatorial Multi-Armed Bandit and Its Extension to Probabilistically Triggered Arms (2014)Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems (2012)Adaptive Game Playing Using Multiplicative Weights (1999)Online convex optimization in the bandit setting: gradient descent without a gradient (2004)Multi-armed Bandit Algorithms and Empirical Evaluation (2005)
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References

  • 2002Finite-time Analysis of the Multiarmed Bandit Problem5,980 cited
  • 1952Some aspects of the sequential design of experiments2,183 cited
  • 2002Gambling in a rigged casino: The adversarial multi-armed bandit problem741 cited
  • 2008Stochastic Linear Optimization Under Bandit Feedback581 cited
  • 2009Exploration–exploitation tradeoff using variance estimates in multi-armed bandits571 cited
  • 1995Sample mean based index policies byO(logn) regret for the multi-armed bandit problem539 cited
  • 2010Linearly Parameterized Bandits428 cited
  • 1987Asymptotically efficient allocation rules for the multiarmed bandit problem with multiple plays-Part I: I.I.D. rewards358 cited
  • 2012Combinatorial bandits320 cited
  • 2008On Upper-Confidence Bound Policies for Non-Stationary Bandit Problems172 cited
  • 2007Tuning Bandit Algorithms in Stochastic Environments158 cited
  • 2006Regret Minimization Under Partial Monitoring138 cited
  • 1988Asymptotically efficient adaptive allocation rules for the multiarmed bandit problem with switching cost112 cited
  • 2002Using upper confidence bounds for online learning53 cited
  • 2010Decentralized multi-armed bandit with multiple distributed players

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  • 20161Joint Channel Selection and Power Control in Infrastructureless Wireless Networks: A Multi-Player Multi-Armed Bandit Framework46 cited