Results 31 to 40 of about 3,605,404 (198)
Probability Matching and Reinforcement Learning
, 2011 Probability matching occurs when an action is chosen with a frequency equivalent to the probability of that action being the best choice. This sub-optimal behavior has been reported repeatedly by psychologist and experimental economist.
Javier Rivas (6635951)
core +5 more sources
Objective Bayesian Inference for Differential Effects in Unequal-Variance Two-Sample Normal Models
MathematicsIn this paper, we develop a unified objective Bayesian framework for inference on the differential effect in the unequal-variance two-sample normal model.
Sang Gil Kang, Yongku Kim
doaj +1 more source
, 2021 In this paper reference and probability-matching priors are derived for the univariate Student $t$-distribution. These priors generally lead to procedures with properties frequentists can relate to while still retaining Bayes validity. The priors are tested by performing simulation studies.
van der Merwe, A. J. +2 more
openaire +2 more sources
Estimation of Geometric Mean for k Exponential Parameters Using a Probability Matching Prior [PDF]
Communications for Statistical Applications and Methods, 2003 In this article, we consider a Bayesian estimation method for the geometric mean of exponential parameters, Using the Tibshirani's orthogonal parameterization, we suggest an invariant prior distribution of the parameters. It is seen that the prior, probability matching prior, is better than the uniform prior in the sense of correct frequentist coverage
Hea-Jung Kim, Dae Hwang Kim
openaire +1 more source
Bladder management in patients undergoing spine surgery: An assessment of care delivery
North American Spine Society Journal, 2021 Background: Lower urinary tract dysfunction is common in the early postoperative phase after spine surgery. Although it is essential for an optimal patient management to balance benefits and harms, it is not known which patient benefit from a ...
Lorenz Leitner +6 more
doaj +1 more source
An Enhanced Local Optimization Algorithm for GNSS Shadow Matching in Mobile Phones
Remote SensingIn the context of mobile phones, the local optimal global navigation satellite systems (GNSS) shadow matching algorithm, which is based on the urban three-dimensional model, can effectively reduce the error of GNSS pseudo-range single-point positioning ...
Xianggeng Han +6 more
doaj +1 more source
On the origins of suboptimality in human probabilistic inference.
PLoS Computational Biology, 2014 Humans have been shown to combine noisy sensory information with previous experience (priors), in qualitative and sometimes quantitative agreement with the statistically-optimal predictions of Bayesian integration.
Luigi Acerbi +2 more
doaj +1 more source
Visual Point Cloud Map Construction and Matching Localization for Autonomous Vehicle
DronesCollaboration between autonomous vehicles and drones can enhance the efficiency and connectivity of three-dimensional transportation systems. When satellite signals are unavailable, vehicles can achieve accurate localization by matching rich ground ...
Shuchen Xu +4 more
doaj +1 more source
Bayesian regression explains how human participants handle parameter uncertainty.
PLoS Computational Biology, 2020 Accumulating evidence indicates that the human brain copes with sensory uncertainty in accordance with Bayes' rule. However, it is unknown how humans make predictions when the generative model of the task at hand is described by uncertain parameters ...
Jannes Jegminat +4 more
doaj +1 more source
SemGeoFrame: A Visual Matching Framework for Aircraft Based on Surface Semantic Information
Remote SensingIn GNSS-denied environments, UAV visual positioning faces the critical bottleneck of low matching accuracy between heterogeneous images. To address this, we propose SemGeoFrame, a visual matching framework that leverages surface semantic information to ...
Zhaoyun Luo +6 more
doaj +1 more source