Results 31 to 40 of about 341,773 (269)
The Bayesian lens and Bayesian blinkers
Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 2023 I discuss the benefits of looking through the ‘Bayesian lens’ (seeking a Bayesian interpretation of ostensibly non-Bayesian methods), and the dangers of wearing ‘Bayesian blinkers’ (eschewing non-Bayesian methods as a matter of philosophical principle).
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Bayesian Exploration: Incentivizing Exploration in Bayesian Games [PDF]
Operations Research, 2016 In a wide range of recommendation systems, self-interested individuals (“agents”) make decisions over time, using information revealed by other agents in the past, and producing information that may help agents in the future. Each agent would like to exploit the best action given the current information but would prefer the previous agents to explore ...
Yishay Mansour +3 more
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Proceedings of the AAAI Conference on Artificial Intelligence, 2019 We consider the problem of how decision making can be fair when the underlying probabilistic model of the world is not known with certainty. We argue that recent notions of fairness in machine learning need to explicitly incorporate parameter uncertainty, hence we introduce the notion of Bayesian fairness as a suitable candidate for fair decision rules.
Dimitrakakis, C. (Christos) +3 more
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Bayesian Multilateration [PDF]
IEEE Signal Processing Letters, 2021 Multilateration (MLAT) is the de facto standard to localize points of interest (POIs) in navigation and surveillance systems. Despite sensors being inherently noisy, most existing techniques i) are oblivious to noise patterns in sensor measurements; and ii) only provide point estimates of the POI’s location.
Sampaio de Carvalho Alencar, Alisson +4 more
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Statistical Theory and Related Fields, 2019 Demographic estimation becomes a problem of small area estimation when detailed disaggregation leads to small cell counts. The usual difficulties of small area estimation are compounded when the available data sources contain measurement errors.
Junni L. Zhang, John Bryant
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Computing for Numeracy: How Safe is Your COVID-19 Social Bubble?
Numeracy, 2021 The COVID-19 pandemic has led many people to form social bubbles. These social bubbles are small groups of people who interact with one another but restrict interactions with the outside world.
Charles Connor
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Çanakkale Onsekiz Mart University Journal of Marine Sciences and Fisheries, 2022 Time series of catch and effort data for Farfantepenaeus notialis were analysed in ‘R’ using a data limited state-space Bayesian Catch-maximum Sustainbale Yield (CMSY) method for stock assessment from catch (tonnes) and abundance data (t/day).
Komba J. Konoyima
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Thou Shalt Not Squander Life – Comparing Five Approaches to Argument Strength
Studies in Logic, Grammar and Rhetoric, 2023 Different approaches analyze the strength of a natural language argument in different ways. This paper contrasts the dialectical, structural, probabilistic (or Bayesian), computational, and empirical approaches by exemplarily applying them to a single ...
Zenker Frank +4 more
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Epidemiology, Biostatistics and Public Health, 2023 Background: Because of its convenience and robustness, the generalized estimating equations (GEE) method has been commonly used to fit marginal models of continuous outcomes in family studies.
Xi Chen +8 more
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Bayesian and empirical Bayesian forests
, 2015 We derive ensembles of decision trees through a nonparametric Bayesian model, allowing us to view random forests as samples from a posterior distribution. This insight provides large gains in interpretability, and motivates a class of Bayesian forest (BF) algorithms that yield small but reliable performance gains. Based on the BF framework, we are able
Matthew Taddy +3 more
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