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Toward Optimal Adaptive Online Shortest Path Routing With Acceleration Under Jamming Attack
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Toward Optimal Adaptive Online Shortest Path Routing With Acceleration Under Jamming Attack (2019)Toward Optimal Adaptive Online Shortest P…Tight Regret Bounds for Stochastic Combinatorial Semi-Bandits (2014)Tight Regret Bounds for Stoch…Regret in Online Combinatorial Optimization (2013)Regret in Online Combinatoria…Kullback–Leibler upper confidence bounds for optimal sequential allocation (2013)Kullback–Leibler upper confid…KULLBACK-LEIBLER UPPER CONFIDENCE BOUNDS FOR OPTIMAL SEQUENTIAL ALLOCATION (2013)KULLBACK-LEIBLER UPPER CONFID…The best of both worlds: stochastic and adversarial bandits (2012)The best of both worlds: stoc…Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems (2012)Regret Analysis of Stochastic…Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems (2012)Regret Analysis of Stochastic…Combinatorial Network Optimization With Unknown Variables: Multi-Armed Bandits With Linear Rewards and Individual Observations (2012)Combinatorial Network Optimiz…Combinatorial bandits (2012)Combinatorial banditsStochastic Linear Optimization Under Bandit Feedback (2008)Stochastic Linear Optimizatio…The on-line shortest path problem under partial monitoring (2007)The on-line shortest path pro…Minimax policies for adversarial and stochastic bandits (2004)Minimax policies for adversar…Adaptive routing with end-to-end feedback (2004)Adaptive routing with end-to-…The Nonstochastic Multiarmed Bandit Problem (2002)The Nonstochastic Multiarmed …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…Prediction, Learning, and Games (2006)UCB revisited: Improved regret bounds for the stochastic multi-armed bandit problem (2010)Further Optimal Regret Bounds for Thompson Sampling (2012)A Stochastic Approximation Method (1951)Introduction to Online Convex Optimization (2016)Introduction to Online Convex Optimization (2016)Introduction to Multi-Armed Bandits (2019)Some aspects of the sequential design of experiments (1952)A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting (1997)Online Learning and Online Convex Optimization (2011)Online Learning and Online Convex Optimization (2012)Using confidence bounds for exploitation-exploration trade-offs (2003)Combinatorial Multi-Armed Bandit and Its Extension to Probabilistically Triggered Arms (2014)Decentralized Learning for Multiplayer Multiarmed Bandits (2014)Cascading Bandits: Learning to Rank in the Cascade Model (2015)Efficient algorithms for online decision problems (2004)From Bandits to Experts: On the Value of Side-Observations (2011)Multi-Armed Bandit Allocation Indices. (1990)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)Bandit Processes and Dynamic Allocation Indices (1979)From Bandits to Monte-Carlo Tree Search: The Optimistic Principle Applied to Optimization and Planning (2014)Batched bandit problems (2016)Explore First, Exploit Next: The True Shape of Regret in Bandit Problems (2016)Information-Theoretic Regret Bounds for Gaussian Process Optimization in the Bandit Setting (2012)Information-seeking, curiosity, and attention: computational and neural mechanisms (2013)A unified framework for stochastic optimization (2018)Bandit Algorithms (2020)Contextual Bandits with Linear Payoff Functions (2011)Thompson Sampling for Contextual Bandits with Linear Payoffs (2012)Learning to Optimize via Posterior Sampling (2014)
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References

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  • 2002The Nonstochastic Multiarmed Bandit Problem2,210 cited
  • 2012Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems1,410 cited
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  • 2007The on-line shortest path problem under partial monitoring151 cited

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  • 2012The best of both worlds: stochastic and adversarial bandits144 cited
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