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Context effects on probability estimation. [PDF]
PLoS Biology, 2020 Many decisions rely on how we evaluate potential outcomes and estimate their corresponding probabilities of occurrence. Outcome evaluation is subjective because it requires consulting internal preferences and is sensitive to context.
Wei-Hsiang Lin +2 more
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Efficient randomness certification by quantum probability estimation [PDF]
Physical Review Research, 2020 For practical applications of quantum randomness generation, it is important to certify and further produce a fixed block of fresh random bits with as few trials as possible. Consequently, protocols with high finite-data efficiency are preferred.
Yanbao Zhang, Honghao Fu, Emanuel Knill
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Transfer posterior error probability estimation for peptide identification [PDF]
BMC Bioinformatics, 2020 Background In shotgun proteomics, database searching of tandem mass spectra results in a great number of peptide-spectrum matches (PSMs), many of which are false positives.
Xinpei Yi, Fuzhou Gong, Yan Fu
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Using cognitive models to combine probability estimates [PDF]
Judgment and Decision Making, 2014 We demonstrate the usefulness of cognitive models for combining human estimates of probabilities in two experiments. The first experiment involves people’s estimates of probabilities for general knowledge questions such as “What percentage of the world’s
Michael D. Lee, Irina Danileiko
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Machine learning approaches for the prediction of serious fluid leakage from hydrocarbon wells
Data-Centric Engineering, 2023 The exploitation of hydrocarbon reservoirs may potentially lead to contamination of soils, shallow water resources, and greenhouse gas emissions. Fluids such as methane or CO2 may in some cases migrate toward the groundwater zone and atmosphere through ...
Mehdi Rezvandehy, Bernhard Mayer
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Estimating subjective probabilities [PDF]
Journal of Risk and Uncertainty, 2014 Subjective probabilities play a central role in many economic decisions, and act as an immediate confound of inferences about behavior, unless controlled for. Several procedures to recover subjective probabilities have been proposed, but in order to recover the correct latent probability one must either construct elicitation mechanisms that control for
Andersen, S. +3 more
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Estimation with Uncertainty via Conditional Generative Adversarial Networks
Sensors, 2021 Conventional predictive Artificial Neural Networks (ANNs) commonly employ deterministic weight matrices; therefore, their prediction is a point estimate.
Minhyeok Lee, Junhee Seok
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A Witness Function Based Construction of Discriminative Models Using Hermite Polynomials
Frontiers in Applied Mathematics and Statistics, 2020 In machine learning, we are given a dataset of the form {(xj,yj)}j=1M, drawn as i.i.d. samples from an unknown probability distribution μ; the marginal distribution for the xj's being μ*, and the marginals of the kth class μk*(x) possibly overlapping. We
Hrushikesh N. Mhaskar +2 more
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Kernel-Based Analysis of Massive Data
Frontiers in Applied Mathematics and Statistics, 2020 Dealing with massive data is a challenging task for machine learning. An important aspect of machine learning is function approximation. In the context of massive data, some of the commonly used tools for this purpose are sparsity, divide-and-conquer ...
Hrushikesh N. Mhaskar
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Multivariate Combined Collision Detection for Multi-Unmanned Aircraft Systems
IEEE Access, 2022 To mitigate the problem of multiple unmanned aircraft systems (MUAS) conflicts at low altitude and ensure the operational safety, this paper proposes a Multivariate Combined Conflict Detection (MCCD) method for MUAS by combining the characteristics of ...
Honghai Zhang +4 more
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