'Deep Nonparametric Quantile Regression under Covariate Shift', by Xingdong Feng, Xin He, Yuling Jiao, Lican Kang, Caixing Wang.

http://jmlr.org/papers/v25/24-0906.html

#quantile #nonparametric #reweighted

Deep Nonparametric Quantile Regression under Covariate Shift

'Value-Distributional Model-Based Reinforcement Learning', by Carlos E. Luis, Alessandro G. Bottero, Julia Vinogradska, Felix Berkenkamp, Jan Peters.

http://jmlr.org/papers/v25/23-0913.html

#reinforcement #quantile #learns

Value-Distributional Model-Based Reinforcement Learning

#statstab #202 Distribution regression in #R @vincentab

Thoughts: "distribution regression...allows us to measure the association b/w the predictor of interest and the outcome at different quantiles of the outcome"

#regression #marginaleffects #quantile

https://arelbundock.com/posts/distribution_regression/

Distribution regression in R – Vincent Arel-Bundock

'Continuous Prediction with Experts' Advice', by Nicholas J. A. Harvey, Christopher Liaw, Victor S. Portella.

http://jmlr.org/papers/v25/22-0803.html

#stochastic #prediction #quantile

Continuous Prediction with Experts' Advice

'An Analysis of Quantile Temporal-Difference Learning', by Mark Rowland et al.

http://jmlr.org/papers/v25/23-0154.html

#quantile #reinforcement #stochastic

An Analysis of Quantile Temporal-Difference Learning

'Nonparametric Estimation of Non-Crossing Quantile Regression Process with Deep ReQU Neural Networks', by Guohao Shen, Yuling Jiao, Yuanyuan Lin, Joel L. Horowitz, Jian Huang.

http://jmlr.org/papers/v25/22-0488.html

#quantile #nonparametric #estimation

Nonparametric Estimation of Non-Crossing Quantile Regression Process with Deep ReQU Neural Networks

'Localized Debiased Machine Learning: Efficient Inference on Quantile Treatment Effects and Beyond', by Nathan Kallus, Xiaojie Mao, Masatoshi Uehara.

http://jmlr.org/papers/v25/23-0661.html

#quantile #inference #estimation

Localized Debiased Machine Learning: Efficient Inference on Quantile Treatment Effects and Beyond

'Confidence Intervals and Hypothesis Testing for High-dimensional Quantile Regression: Convolution Smoothing and Debiasing', by Yibo Yan, Xiaozhou Wang, Riquan Zhang.

http://jmlr.org/papers/v24/22-1217.html

#quantile #lasso #regression

Confidence Intervals and Hypothesis Testing for High-dimensional Quantile Regression: Convolution Smoothing and Debiasing

Expected Pinball Loss For Quantile Regression And Inverse CDF Estimation

https://openreview.net/forum?id=Eg8Rnb0Hdd

#quantile #quantiles #estimation

Expected Pinball Loss For Quantile Regression And Inverse CDF...

We analyze and improve a recent strategy to train a quantile regression model by minimizing an expected pinball loss over all quantiles. Through an asymptotic convergence analysis, we show that...

OpenReview

Transfer Learning for High-dimensional Quantile Regression with Statistical Guarantee

https://openreview.net/forum?id=d3xwrfAG4V

#quantile #estimators #estimation

Transfer Learning for High-dimensional Quantile Regression with...

The task of transfer learning is to improve estimation/inference of a target model by migrating data from closely related source populations. In this article, we propose transfer learning...

OpenReview