Results 11 to 20 of about 3,431,698 (356)
Distributional Reinforcement Learning with Quantile Regression [PDF]
AAAI Conference on Artificial Intelligence, 2017 In reinforcement learning an agent interacts with the environment by taking actions and observing the next state and reward. When sampled probabilistically, these state transitions, rewards, and actions can all induce randomness in the observed long-term
Bellemare, Marc G. +3 more
core +2 more sources
Can Food Inflation Be Stabilized By Monetary Policy? A Quantile Regression Approach
Journal of economic impact, 2022 Theoretically, a consistent and well-defined monetary policy can stabilize food inflation. However, empirical findings have reported both positive and negative effects of monetary policy measures on food inflation.
Choudary Ihtasham Ali +5 more
openalex +3 more sources
Nonparametric Multiple-Output Center-Outward Quantile Regression [PDF]
Journal of the American Statistical Association, 2022 Building on recent measure-transportation-based concepts of multivariate quantiles, we are considering the problem of nonparametric multiple-output quantile regression.
Eustasio del Barrio +2 more
openalex +3 more sources
Scalable Membership Inference Attacks via Quantile Regression [PDF]
Neural Information Processing Systems, 2023 Membership inference attacks are designed to determine, using black box access to trained models, whether a particular example was used in training or not. Membership inference can be formalized as a hypothesis testing problem.
Martín Bertrán +5 more
semanticscholar +1 more source
Functional-Coefficient Quantile Regression for Panel Data with Latent Group Structure [PDF]
Journal of business & economic statistics, 2023 This article considers estimating functional-coefficient models in panel quantile regression with individual effects, allowing the cross-sectional and temporal dependence for large panel observations.
Xiao-rong Yang +3 more
semanticscholar +1 more source
Modified Quantile Regression for Modeling the Low Birth Weight
Frontiers in Applied Mathematics and Statistics, 2022 This study aims to identify the best model of low birth weight by applying and comparing several methods based on the quantile regression method's modification.
Ferra Yanuar +2 more
doaj +1 more source
Ensemble Conformalized Quantile Regression for Probabilistic Time Series Forecasting [PDF]
IEEE Transactions on Neural Networks and Learning Systems, 2022 This article presents a novel probabilistic forecasting method called ensemble conformalized quantile regression (EnCQR). EnCQR constructs distribution-free and approximately marginally valid prediction intervals (PIs), which are suitable for ...
Vilde Jensen, F. Bianchi, S. N. Anfinsen
semanticscholar +1 more source
A Bayesian Binary reciprocal LASSO quantile regression (with practical application)
Journal of Kufa for Mathematics and Computer, 2023 Quantile regression is one of the methods that has taken a wide space in application in the previous two decades because of the attractive features of these methods to researchers, as it is not affected by outliers values, meaning that it is considered ...
Mohammed Kahnger, Ahmad Naeem Flaih
doaj +1 more source
Cauchy: Jurnal Matematika Murni dan Aplikasi, 2021 This study aims to construct the model for the length of hospital stay for patients with COVID-19 using quantile regression and Bayesian quantile approaches.
Ferra Yanuar +4 more
doaj +1 more source
Pyramid Quantile Regression [PDF]
Journal of Computational and Graphical Statistics, 2019 Quantile regression models provide a wide picture of the conditional distributions of the response variable by capturing the effect of the covariates at different quantile levels. In most applications, the parametric form of those conditional distributions is unknown and varies across the covariate space, so fitting the given quantile levels ...
T. Rodrigues +2 more
openaire +4 more sources