Results 31 to 40 of about 4,126,170 (169)
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
Online‐optimized RAG for tool use and function calling
Decision Sciences, EarlyView.Abstract In many applications, retrieval‐augmented generation (RAG) drives tool use and function calling by embedding the (user) queries and matching them to prespecified tool/function descriptions. In this article, we address an embedding misalignment issue that often arises in practical applications due to imperfect embedding models or noisy ...
Yu Pan, Xiaocheng Li, Hanzhao Wang
wiley +1 more source
Machine Learning and Knowledge ExtractionAdaptive decision-making has emerged as an important direction in audio classification. Reinforcement learning (RL) and multi-armed bandit (MAB) methods offer principled frameworks for sequential and localized decision-making.
Geofrey Owino +2 more
doaj +1 more source
Algorithmic Monoculture and Its Critics
Philosophical Perspectives, EarlyView.ABSTRACT Algorithmic decision‐making is replacing idiosyncratic human judgment in domains such as hiring, lending, and criminal justice. This shift promises increased consistency, but many scholars worry that it can go too far. They warn of the dangers of algorithmic monoculture, in which all decisions across a domain are made using a single algorithm.
Brian Hedden, Manish Raghavan
wiley +1 more source
LLM-Guided Ensemble Learning for Contextual Bandits with Copula and Gaussian Process Models
MathematicsContextual multi-armed bandits (CMABs) are vital for sequential decision-making in areas such as recommendation systems, clinical trials, and finance. We propose a simulation framework integrating Gaussian Process (GP)-based CMABs with vine copulas to ...
Jong-Min Kim
doaj +1 more source
A Survey on Practical Applications of Multi-Armed and Contextual Bandits
CoRR, 2019 under review by IJCAI 2019 ...
Djallel Bouneffouf 0001, Irina Rish
openaire +2 more sources
Computational Modeling of Decision Making Enhances the Adversity Researcher's Toolbox
Topics in Cognitive Science, EarlyView.Abstract Over the past decades, there has been major progress in our understanding of how adversity influences cognitive abilities and strategies. However, most of this research is based on raw performance, such as response times and accuracy. These measures are informative about decision‐making outcomes but tell us little about cognitive processes. In
Stefan Vermeent +2 more
wiley +1 more source
Efficient crowdsourcing of unknown experts using multi-armed bandits [PDF]
, 2012 We address the expert crowdsourcing problem, in which an employer wishes to assign tasks to a set of available workers with heterogeneous working costs.
Tran-Thanh, Long +11 more
core +1 more source
Knapsack based optimal policies for budget-limited multi-armed bandits
, 2012 In budget-limited multi-armed bandit (MAB) problems, the learner’s actions are costly and constrained by a fixed budget. Consequently, an optimal exploitation policy may not be to pull the optimal arm repeatedly, as is the case in other variants of MAB ...
Tran-Thanh, Long +4 more
core +1 more source
A Comprehensive Review on Federated and Incremental Learning in Spatial Crowdsourcing Systems
WIREs Data Mining and Knowledge Discovery, Volume 16, Issue 4, December 2026.A comprehensive overview of Federated and Incremental Learning (FIL) integration in Spatial Crowdsourcing, highlighting privacy, security, adaptability, efficiency challenges, and future research directions. ABSTRACT Spatial Crowdsourcing (SC) coordinates workers and requesters through personal mobile devices to complete location‐dependent tasks in ...
Md Mujibur Rahman +3 more
wiley +1 more source