Toward Optimal Adaptive Online Shortest Path Routing With Acceleration Under Jamming Attack
暂无分享,去创建一个
Pan Zhou | Jie Xu | Wei Wang | Dapeng Oliver Wu | Yuchong Hu | Shouling Ji | S. Ji | Yuchong Hu | Wei Wang | Pan Zhou | Jie Xu
[1] T. Javidi,et al. No Regret Routing for ad-hoc wireless networks , 2010, 2010 Conference Record of the Forty Fourth Asilomar Conference on Signals, Systems and Computers.
[2] Wenyuan Xu,et al. Jamming-Resilient Multipath Routing , 2012, IEEE Transactions on Dependable and Secure Computing.
[3] Peter Auer,et al. Finite-time Analysis of the Multiarmed Bandit Problem , 2002, Machine Learning.
[4] Baruch Awerbuch,et al. Adaptive routing with end-to-end feedback: distributed learning and geometric approaches , 2004, STOC '04.
[5] John Shawe-Taylor,et al. PAC-Bayes-Bernstein Inequality for Martingales and its Application to Multiarmed Bandits , 2011, ICML On-line Trading of Exploration and Exploitation.
[6] Thomas P. Hayes,et al. Stochastic Linear Optimization under Bandit Feedback , 2008, COLT.
[7] Jean-Yves Audibert,et al. Minimax Policies for Adversarial and Stochastic Bandits. , 2009, COLT 2009.
[8] Zhongcheng Li,et al. Almost Optimal Channel Access in Multi-Hop Networks with Unknown Channel Variables , 2013, 2014 IEEE 34th International Conference on Distributed Computing Systems.
[9] Donald F. Towsley,et al. Endhost-based shortest path routing in dynamic networks: An online learning approach , 2013, 2013 Proceedings IEEE INFOCOM.
[10] Gábor Lugosi,et al. Concentration Inequalities - A Nonasymptotic Theory of Independence , 2013, Concentration Inequalities.
[11] Gilles Stoltz. Incomplete information and internal regret in prediction of individual sequences , 2005 .
[12] Baruch Awerbuch,et al. Provably competitive adaptive routing , 2005, Proceedings IEEE 24th Annual Joint Conference of the IEEE Computer and Communications Societies..
[13] Richard S. Sutton,et al. Reinforcement Learning: An Introduction , 1998, IEEE Trans. Neural Networks.
[14] Aleksandrs Slivkins,et al. One Practical Algorithm for Both Stochastic and Adversarial Bandits , 2014, ICML.
[15] Bhaskar Krishnamachari,et al. Combinatorial Network Optimization With Unknown Variables: Multi-Armed Bandits With Linear Rewards and Individual Observations , 2010, IEEE/ACM Transactions on Networking.
[16] Peng Ning,et al. Jamming-Resistant Multiradio Multichannel Opportunistic Spectrum Access in Cognitive Radio Networks , 2016, IEEE Transactions on Vehicular Technology.
[17] Andrew S. Tanenbaum,et al. Computer networks, 4th Edition , 2002 .
[18] Peter Auer,et al. An algorithm with nearly optimal pseudo-regret for both stochastic and adversarial bandits , 2016, COLT.
[19] Sébastien Bubeck,et al. Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems , 2012, Found. Trends Mach. Learn..
[20] András György,et al. The Combination of the Label Efficient and the Multi-Armed Bandit Problem in Adversarial Setting , 2006 .
[21] Nicolò Cesa-Bianchi,et al. Finite-Time Regret Bounds for the Multiarmed Bandit Problem , 1998, ICML.
[22] Magyar Tud. The On-Line Shortest Path Problem Under Partial Monitoring , 2007 .
[23] Ming Li,et al. Jamming Resilient Communication Using MIMO Interference Cancellation , 2016, IEEE Transactions on Information Forensics and Security.
[24] R. Munos,et al. Kullback–Leibler upper confidence bounds for optimal sequential allocation , 2012, 1210.1136.
[25] Ohad Shamir,et al. Optimal Distributed Online Prediction Using Mini-Batches , 2010, J. Mach. Learn. Res..
[26] Nicolò Cesa-Bianchi,et al. Gambling in a rigged casino: The adversarial multi-armed bandit problem , 1995, Proceedings of IEEE 36th Annual Foundations of Computer Science.
[27] Aleksandrs Slivkins,et al. 25th Annual Conference on Learning Theory The Best of Both Worlds: Stochastic and Adversarial Bandits , 2022 .
[28] T. L. Lai Andherbertrobbins. Asymptotically Efficient Adaptive Allocation Rules , 1985 .
[29] Gábor Lugosi,et al. Minimizing Regret with Label Efficient Prediction , 2004, COLT.
[30] Dapeng Wu,et al. Shortest Path Routing in Unknown Environments: Is the Adaptive Optimal Strategy Available? , 2016, 2016 13th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON).
[31] Qing Zhao,et al. Online learning for stochastic linear optimization problems , 2012, 2012 Information Theory and Applications Workshop.
[32] Nicolò Cesa-Bianchi,et al. Combinatorial Bandits , 2012, COLT.
[33] Guey-Yun Chang,et al. A Jamming-Resistant Channel Hopping Scheme for Cognitive Radio Networks , 2017, IEEE Transactions on Wireless Communications.
[34] W. R. Thompson. ON THE LIKELIHOOD THAT ONE UNKNOWN PROBABILITY EXCEEDS ANOTHER IN VIEW OF THE EVIDENCE OF TWO SAMPLES , 1933 .
[35] Mr. Jamal Mhawesh Challab. Adaptive Opportunistic Routing For Wireless AD HOC Networks , 2016 .
[36] Ambuj Tewari,et al. Online Bandit Learning against an Adaptive Adversary: from Regret to Policy Regret , 2012, ICML.
[37] Peter Auer,et al. The Nonstochastic Multiarmed Bandit Problem , 2002, SIAM J. Comput..
[38] Gábor Lugosi,et al. Regret in Online Combinatorial Optimization , 2012, Math. Oper. Res..
[39] Qing Zhao,et al. Adaptive shortest-path routing under unknown and stochastically varying link states , 2012, 2012 10th International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt).
[40] Richard Combes,et al. Stochastic Online Shortest Path Routing: The Value of Feedback , 2013, IEEE Transactions on Automatic Control.
[41] András György,et al. Online Learning under Delayed Feedback , 2013, ICML.
[42] Koby Crammer,et al. Prediction with Limited Advice and Multiarmed Bandits with Paid Observations , 2014, ICML.
[43] Zheng Wen,et al. Tight Regret Bounds for Stochastic Combinatorial Semi-Bandits , 2014, AISTATS.