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Cooperative multi-agent decision making involves a group of agents cooperatively solving learning problems while communicating over a network with delays.
Cooperative online learning: Keeping your neighbors updated
Cesa-Bianchi, N., Cesari, T. R., and Monteleoni, C · 1901
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On the evolution of random graphs
Erdős, P. and Rényi, A · 1960
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Hadamard products and multivariate statistical analysis
Styan, G. P · 1973
Earlier work this paper cites.
Asynchronous consensus and broadcast protocols
Bracha, G. and Toueg, S · 1985
Earlier work this paper cites.
Locality in distributed graph algorithms
Linial, N · 1992
Earlier work this paper cites.
Finite-time analysis of the multiarmed bandit problem
Auer, P., Cesa-Bianchi, N., and Fischer, P · 2002
Earlier work this paper cites.
Rademacher and gaussian complexities: Risk bounds and structural results
Bartlett, P. L. and Mendelson, S · 2002
Earlier work this paper cites.
On delayed prediction of individual sequences
Weinberger, M. J. and Ordentlich, E · 2002
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On the kronecker product
Schake, K · 2004
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Survivability of multiagent-based supply networks: a topological perspect
Thadakamaila, H., Raghavan, U. N., Kumara, S., and Albert, R · 2004
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Support vector machines and kernel algorithms
Schölkopf, B. and Smola, A · 2005
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Clustknn: a highly scalable hybrid model-& memory-based cf algorithm
Al Mamunur Rashid, S. K. L., Karypis, G., and Riedl, J · 2006
Earlier work this paper cites.
A hilbert space embedding for distributions
Smola, A., Gretton, A., Song, L., and Schölkopf, B · 2007
Earlier work this paper cites.
Online linear optimization and adaptive routing
Awerbuch, B. and Kleinberg, R · 2008
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Gaussian process optimization in the bandit setting: No regret and experimental design
Srinivas, N., Krause, A., Kakade, S. M., and Seeger, M · 2009
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Universal kernels on non-standard input spaces
Christmann, A. and Steinwart, I · 2010
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A contextual-bandit approach to personalized news article recommendation
Li, L., Chu, W., Langford, J., and Schapire, R. E · 2010
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Distributed learning in multi-armed bandit with multiple players
Liu, K. and Zhao, Q · 2010
Earlier work this paper cites.
Online markov decision processes under bandit feedback
Neu, G., Antos, A., György, A., and Szepesvári, C · 2010
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Improved algorithms for linear stochastic bandits
Abbasi-Yadkori, Y., Pál, D., and Szepesvári, C · 2011
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Generalizing from several related classification tasks to a new unlabeled sample
Blanchard, G., Lee, G., and Scott, C · 2011
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Contextual bandits with linear payoff functions
Chu, W., Li, L., Reyzin, L., and Schapire, R · 2011
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Contextual gaussian process bandit optimization
Krause, A. and Ong, C. S · 2011
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Analysis of thompson sampling for the multi-armed bandit problem
Agrawal, S. and Goyal, N · 2012
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Regret analysis of stochastic and nonstochastic multi-armed bandit problems
Bubeck, S., Cesa-Bianchi, N., et al · 2012
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On distributed cooperative decision-making in multiarmed bandits
Landgren, P., Srivastava, V., and Leonard, N. E · 2016
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Distributed cooperative decision-making in multiarmed bandits: Frequentist and bayesian algorithms
Landgren, P., Srivastava, V., and Leonard, N. E · 2016
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Snap: A general-purpose network analysis and graph-mining library
Leskovec, J. and Sosič, R · 2016
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Collaborative filtering bandits
Li, S., Karatzoglou, A., and Gentile, C · 2016
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On kernelized multi-armed bandits
Chowdhury, S. R. and Gopalan, A · 2017
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Multi-task learning for contextual bandits
Deshmukh, A. A., Dogan, U., and Scott, C · 2017
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A kernel two-sample test
Gretton, A., Borgwardt, K. M., Rasch, M. J., Schölkopf, B., and Smola, A · 2012
Cited alongside, same era.
Matrix analysis
Horn, R. A. and Johnson, C. R · 2012
Cited alongside, same era.
A gang of bandits
Cesa-Bianchi, N., Gentile, C., and Zappella, G · 2013
Cited alongside, same era.
Online learning under delayed feedback
Joulani, P., Gyorgy, A., and Szepesvári, C · 2013
Cited alongside, same era.
Survey of local algorithms
Suomela, J · 2013
Cited alongside, same era.
Gossip-based distributed stochastic bandit algorithms
Szorenyi, B., Busa-Fekete, R., Hegedus, I., Ormandi, R., Jelasity, M., and Kegl, B · 2013
Cited alongside, same era.
On context-dependent clustering of bandits
Gentile, C., Li, S., Kar, P., Karatzoglou, A., Zappella, G., and Etrue, E · 2017
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Lower bounds on regret for noisy gaussian process bandit optimization
Scarlett, J., Bogunovic, I., and Cevher, V · 2017
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mumab: A multi-armed bandit model for wireless network selection
Boldrini, S., De Nardis, L., Caso, G., Le, M. T., Fiorina, J., and Di Benedetto, M.-G · 2018
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Social imitation in cooperative multiarmed bandits: Partition-based algorithms with strictly local information
Landgren, P., Srivastava, V., and Leonard, N. E · 2018
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Online clustering of contextual cascading bandits
Li, S. and Zhang, S · 2018
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Kernel-based multi-task contextual bandits in cellular network configuration
Wang, X., Guo, X., Chuai, J., Chen, Z., and Liu, X · 2018
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Individual regret in cooperative nonstochastic multi-armed bandits
Bar-On, Y. and Mansour, Y · 2019
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Gaussian process optimization with adaptive sketching: Scalable and no regret
Calandriello, D., Carratino, L., Lazaric, A., Valko, M., and Rosasco, L · 2019
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Improved algorithm on online clustering of bandits
Li, S., Chen, W., and Leung, K.-S · 2019
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Decentralized cooperative stochastic multi-armed bandits
Martínez-Rubio, D., Kanade, V., and Rebeschini, P · 2019
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Bandit optimisation of functions in the mat \ \backslash ’ern kernel rkhs
Janz, D., Burt, D. R., and González, J · 2020
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Distributed bandit learning: Near-optimal regret with efficient communication
Wang, Y., Hu, J., Chen, X., and Wang, L · 2020
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