Academic literature on the topic 'Sleeping Bandits'

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Journal articles on the topic "Sleeping Bandits"

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Li, Fengjiao, Jia Liu, and Bo Ji. "Combinatorial Sleeping Bandits With Fairness Constraints." IEEE Transactions on Network Science and Engineering 7, no. 3 (2020): 1799–813. http://dx.doi.org/10.1109/tnse.2019.2954310.

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Kleinberg, Robert, Alexandru Niculescu-Mizil, and Yogeshwer Sharma. "Regret bounds for sleeping experts and bandits." Machine Learning 80, no. 2-3 (2010): 245–72. http://dx.doi.org/10.1007/s10994-010-5178-7.

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Choi, Sanghee, and Hyeong Soo Chang. "Combining Multiple Strategies for Sleeping Bandits with Stochastic Rewards and Availability." Journal of KIISE 44, no. 1 (2017): 63–70. http://dx.doi.org/10.5626/jok.2017.44.1.63.

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Chang, Hyeong Soo. "Sleeping experts and bandits approach to constrained Markov decision processes." Automatica 63 (January 2016): 182–86. http://dx.doi.org/10.1016/j.automatica.2015.10.015.

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Mohamed, Ehab Mahmoud, Sherief Hashima, Kohei Hatano, Saud Alhajaj Aldossari, Mahdi Zareei, and Mohamed Rihan. "Two-Hop Relay Probing in WiGig Device-to-Device Networks Using Sleeping Contextual Bandits." IEEE Wireless Communications Letters 10, no. 7 (2021): 1581–85. http://dx.doi.org/10.1109/lwc.2021.3074972.

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Ali, Samad, Aidin Ferdowsi, Walid Saad, Nandana Rajatheva, and Jussi Haapola. "Sleeping Multi-Armed Bandit Learning for Fast Uplink Grant Allocation in Machine Type Communications." IEEE Transactions on Communications 68, no. 8 (2020): 5072–86. http://dx.doi.org/10.1109/tcomm.2020.2989338.

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Li, Le, and Benjamin Guedj. "Sequential Learning of Principal Curves: Summarizing Data Streams on the Fly." Entropy 23, no. 11 (2021): 1534. http://dx.doi.org/10.3390/e23111534.

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When confronted with massive data streams, summarizing data with dimension reduction methods such as PCA raises theoretical and algorithmic pitfalls. A principal curve acts as a nonlinear generalization of PCA, and the present paper proposes a novel algorithm to automatically and sequentially learn principal curves from data streams. We show that our procedure is supported by regret bounds with optimal sublinear remainder terms. A greedy local search implementation (called slpc, for sequential learning principal curves) that incorporates both sleeping experts and multi-armed bandit ingredients
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KOMBA, E. K., S. N. KIBONA, A. K. AMBWENE, J. R. STEVENS, and W. C. GIBSON. "Genetic diversity among Trypanosoma brucei rhodesiense isolates from Tanzania." Parasitology 115, no. 6 (1997): 571–79. http://dx.doi.org/10.1017/s0031182097001856.

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We compared 19 stocks of Trypanosoma brucei rhodesiense collected in 1991 and 1994 from Tanzania with representative stocks from other foci of Rhodesian sleeping sickness in Zambia, Kenya and Uganda. Stocks were characterized by isoenzyme electrophoresis, restriction fragment length polymorphisms in variant surface glycoprotein genes and random amplification of polymorphic DNA; the banding patterns obtained were coded for numerical analysis. In addition, the Tanzanian stocks were compared by pulsed field gel electrophoresis. Overall the Tanzanian stocks formed a homogeneous group and the predo
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Tolar, Jakub, In-Hyun Park, Lily Xia, et al. "Patient-Specific Induced Pluripotent Stem Cells in Hurler Syndrome." Blood 112, no. 11 (2008): 386. http://dx.doi.org/10.1182/blood.v112.11.386.386.

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Abstract Hurler syndrome (HS; mucopolysaccharidosis type I) is caused by severe mutations in the iduronidase (IDUA) gene, leading to multi-organ system dysfunction due to the toxic accumulation of glycosaminoglycans. Although allogeneic hematopoietic cell transplantation (HCT) has been shown to provide the IDUA protein and to reverse many of the manifestations of HS, allogeneic HCT is associated with significant morbidity and mortality. We hypothesized that an advantageous alternative strategy may be to induce gene-corrected autologous pluripotent cells to become hematopoietic stem cells, whic
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Ramirez, Francisco E., Jill Siebold, Kathelyn Antuna, Albert Sanchez, and Neil Nedley. "Abstract 471: Lifestyle Interventions Stop Metabolic Syndrome." Arteriosclerosis, Thrombosis, and Vascular Biology 36, suppl_1 (2016). http://dx.doi.org/10.1161/atvb.36.suppl_1.471.

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Background: Remission of metabolic syndrome has been documented with gastric banding surgery. We document a clinical case of remission with lifestyle interventions. Hypothesis: A long term whole food plant based diet (WFBD) and lifestyle changes could potentially stop the metabolic syndrome. Methods: A 58 year old Caucasian from the US participated of a program in Weimar California. He had a history of diabetes mellitus type 2 for 5 years with peripheral neuropathy for 1.5 years, he took metformin 500 mg bid. He was also hypertensive, he used losartan 50 mg bid and furosemide 40 mg qd. The med
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Dissertations / Theses on the topic "Sleeping Bandits"

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Saha, Aadirupa. "Battle of Bandits: Online Learning from Subsetwise Preferences and Other Structured Feedback." Thesis, 2020. https://etd.iisc.ac.in/handle/2005/5184.

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The elicitation and aggregation of preferences is often the key to making better decisions. Be it a perfume company wanting to relaunch their 5 most popular fragrances, a movie recommender system trying to rank the most favoured movies, or a pharmaceutical company testing the relative efficacies of a set of drugs, learning from preference feedback is a widely applicable problem to solve. One can model the sequential version of this problem using the classical multiarmed-bandit (MAB) (e.g., Auer, 2002) by representing each decision choice as one bandit-arm, or more appropriately as a Dueling-Ba
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Chatterjee, Aritra. "A Study of Thompson Sampling Approach for the Sleeping Multi-Armed Bandit Problem." Thesis, 2017. http://etd.iisc.ac.in/handle/2005/3631.

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The multi-armed bandit (MAB) problem provides a convenient abstraction for many online decision problems arising in modern applications including Internet display advertising, crowdsourcing, online procurement, smart grids, etc. Several variants of the MAB problem have been proposed to extend the basic model to a variety of practical and general settings. The sleeping multi-armed bandit (SMAB) problem is one such variant where the set of available arms varies with time. This study is focused on analyzing the efficacy of the Thompson Sampling algorithm for solving the SMAB problem. Any algorit
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Chatterjee, Aritra. "A Study of Thompson Sampling Approach for the Sleeping Multi-Armed Bandit Problem." Thesis, 2017. http://etd.iisc.ernet.in/2005/3631.

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The multi-armed bandit (MAB) problem provides a convenient abstraction for many online decision problems arising in modern applications including Internet display advertising, crowdsourcing, online procurement, smart grids, etc. Several variants of the MAB problem have been proposed to extend the basic model to a variety of practical and general settings. The sleeping multi-armed bandit (SMAB) problem is one such variant where the set of available arms varies with time. This study is focused on analyzing the efficacy of the Thompson Sampling algorithm for solving the SMAB problem. Any algorit
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Book chapters on the topic "Sleeping Bandits"

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Thomson, Peter. "Across the Sleeping Land." In Sacred Sea. Oxford University Press, 2007. http://dx.doi.org/10.1093/oso/9780195170511.003.0022.

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Siberia is the Sleeping Land, a huge subcontinent barely awakened by the first nomads who arrived here uncounted millennia ago, and still, toward the end of the nineteenth century, so devoid of people that in much of it you could travel hundreds of miles in almost any direction and see no evidence that humans had ever existed. Yet the aim of Tsar Alexander III in committing Russia to carve the longest railroad in the world across this great nowhere was not primarily to provide an avenue for settlement by immigrants from overcrowded and often impoverished European Russia. A hundred years after the railroad’s completion, Siberia remains today one of the least-populated places on earth. No, the primary purpose was empire building. It was a way to gain better access to the region’s dazzling natural riches, which were the property of the tsar; to protect the eastern flank of the empire against Chinese and Japanese designs and provide a launching pad for Russia’s own designs to the east; and to bind together a string of Russian settlements flung out over a contiguous land mass larger than that ever claimed by any other single entity. To accomplish its goal of uniting Vladivostok on the Pacific with Moscow and then St. Petersburg on the Atlantic, Russia had to do something that nearly all engineers at the time judged impossible—carve a passable corridor through a continent’s worth of forest, bog, permafrost, stone, and swamp. The work was done by free peasants, imported labor, and prisoners wielding wooden shovels, specially designed machinery, dynamite to blast through permafrost, and bonfires to melt it. Workers had to contend with plague and cholera, searing arctic winters and blistering summers, and attacks by insects, tigers, and bandits. It took twenty-five years from the first felled tree to the last spike, it cost roughly a billion rubles all told, or perhaps as much as seven billion in today’s dollars, and by the time it was done in 1916, the empire was nearly bankrupt and on the verge of collapse. But to a large extent, the effort to bind together at least Russia itself, if not the larger empire, succeeded.
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Conference papers on the topic "Sleeping Bandits"

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Li, Fengjiao, Jia Liu, and Bo Ji. "Combinatorial Sleeping Bandits with Fairness Constraints." In IEEE INFOCOM 2019 - IEEE Conference on Computer Communications. IEEE, 2019. http://dx.doi.org/10.1109/infocom.2019.8737461.

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Kuchibhotla, Vivek, P. Harshitha, and Divitha Elugoti. "Combinatorial Sleeping Bandits with Fairness Constraints and Long-Term Non-Availability of Arms." In 2020 4th International Conference on Electronics, Communication and Aerospace Technology (ICECA). IEEE, 2020. http://dx.doi.org/10.1109/iceca49313.2020.9297371.

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Ali, Samad, Aidin Ferdowsi, Walid Saad, and Nandana Rajatheva. "Sleeping Multi-Armed Bandits for Fast Uplink Grant Allocation in Machine Type Communications." In 2018 IEEE Globecom Workshops (GC Wkshps). IEEE, 2018. http://dx.doi.org/10.1109/glocomw.2018.8644350.

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Yancey, Kevin P., and Burr Settles. "A Sleeping, Recovering Bandit Algorithm for Optimizing Recurring Notifications." In KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. ACM, 2020. http://dx.doi.org/10.1145/3394486.3403351.

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