Results 71 to 80 of about 492,986 (210)
History, EarlyView.Abstract This article examines the poll tax (Ottoman Turkish cizye; Arabic jizya) levied on non‐Muslim subjects of the Ottoman Empire, not as a fixed, one‐dimensional tax item within the Ottoman fiscal system but as a multi‐layered administrative instrument organized around obligation, exemption and remission.
ÖZLEM BAŞARIR
wiley +1 more source
Contextual Bandits with Similarity Information
J. Mach. Learn. Res., 2009 In a multi-armed bandit (MAB) problem, an online algorithm makes a sequence of choices. In each round it chooses from a time-invariant set of alternatives and receives the payoff associated with this alternative. While the case of small strategy sets is by now well-understood, a lot of recent work has focused on MAB problems with exponentially or ...
openaire +5 more sources
The British Journal of Sociology, EarlyView.ABSTRACT Tracing the early adoption of computer gang databases by the Los Angeles County Sheriff's Department and the Los Angeles Police Department in the 1980s to the deployment of computationally‐assisted surveillance during the Vietnam War, this paper uses a genealogical approach to compare surveillance technologies developed across the arc of ...
Christina Hughes
wiley +1 more source
EE-Net: Exploitation-Exploration Neural Networks in Contextual Bandits [PDF]
, 2022 In this paper, we propose a novel neural exploration strategy in contextual bandits, EE-Net, distinct from the standard UCB-based and TS-based approaches. Contextual multi-armed bandits have been studied for decades with various applications.
He, Jingrui +3 more
core
A Bayesian Approach for Subset Selection in Contextual Bandits
, 2021 Subset selection in Contextual Bandits (CB) is an important task in various applications such as advertisement recommendation. In CB, arms are attached with contexts and thus correlated in the context space.
Du, Chao, Li, Jialian, Zhu, Jun
core +1 more source
Linear Contextual Bandits with Interference
CoRRInterference, a key concept in causal inference, extends the reward modeling process by accounting for the impact of one unit's actions on the rewards of others. In contextual bandit (CB) settings, where multiple units are present in the same round, potential interference can significantly affect the estimation of expected rewards for different arms ...
Yang Xu 0089, Wenbin Lu, Rui Song 0006
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Encrypted Linear Contextual Bandit
, 2021 Contextual bandit is a general framework for online learning in sequential decision-making problems that has found application in a wide range of domains, including recommendation systems, online advertising, and clinical trials. A critical aspect of bandit methods is that they require to observe the contexts --i.e., individual or group-level data ...
Garcelon, Evrard +2 more
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Australian Journal of Politics &History, EarlyView.ABSTRACT This study traces how gambling in Australia changed from a simple form of leisure, enjoyed by all social classes in colonial times, to a billion‐dollar industry driven by political and economic imperatives. Using a case study, it links vertical fiscal imbalance (VFI), caused by changes to the state‐federal taxation structure, to the ...
Barbara Kinder, Michael B. Charles
wiley +1 more source
Contextual Bandits with Side-Observations
CoRR, 2020 under ...
Rahul Singh 0001 +3 more
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Distributionally Robust Batch Contextual Bandits
Management Science, 2023 Policy learning using historical observational data are an important problem that has widespread applications. Examples include selecting offers, prices, or advertisements for consumers; choosing bids in contextual first-price auctions; and selecting medication based on patients’ characteristics.
Nian Si +3 more
openaire +4 more sources