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Sökning: WFRF:(Parkes C.) > Konferensbidrag

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  • Dimitrakakis, Christos, 1975, et al. (författare)
  • Bayesian Fairness
  • 2019
  • Ingår i: THIRTY-THIRD AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE / THIRTY-FIRST INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE / NINTH AAAI SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE. - 9781577358091 ; , s. 509-516
  • Konferensbidrag (refereegranskat)abstract
    • 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. Using balance, a definition of fairness introduced in (Kleinberg, Mullainathan, and Raghavan 2016), we show how a Bayesian perspective can lead to well-performing and fair decision rules even under high uncertainty.
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  • Dimitrakakis, Christos, 1975, et al. (författare)
  • Multi-view decision processes: The helper-AI problem
  • 2017
  • Ingår i: Advances in Neural Information Processing Systems. - 1049-5258. ; 2017-December, s. 5444-5453
  • Konferensbidrag (refereegranskat)abstract
    • © 2017 Neural information processing systems foundation. All rights reserved. We consider a two-player sequential game in which agents have the same reward function but may disagree on the transition probabilities of an underlying Markovian model of the world. By committing to play a specific policy, the agent with the correct model can steer the behavior of the other agent, and seek to improve utility. We model this setting as a multi-view decision process, which we use to formally analyze the positive effect of steering policies. Furthermore, we develop an algorithm for computing the agents' achievable joint policy, and we experimentally show that it can lead to a large utility increase when the agents' models diverge.
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  • Quaglia, Milena, et al. (författare)
  • The EMPIR project : Innovative measurements for improved diagnosis and management of neurodegenerative diseases (NeuroMet)
  • 2017
  • Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
    • An initial review of previous studies relating to Alzheimer disease state indices was carried out at RI.SE with the aim to identify additional data to be included in this study and provide generic guidelines for metrological quality assurance of clinical neuropsychological data.Work to utilise new cognitive data to re-analyse correlation studies between MMSE and MRI estimates of grey-matter volume has in this first report of the EMPIR NeuroMet project mainly be done at RI.SE using initially data from earlier studies. Rasch analysis reveals significant distortion of MMSE scales. That in turn leads to a re-evaluation of correlations and decisions (e.g. about health) based on those correlations.
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