Lan Wang

A Variable Lavrent’ev Regularized Collocation Method for Auto-Convolution Volterra Integral Equations of the First Kind

Lan Wang, Hui Liang, Ye Zhang

cn (code pays fourni par la source)

Uniform Bahadur representation of the backfitting estimator for additive quantile models and its applications

Efang Kong, Lan Wang, Yichao Wu

This work is concerned with the Backfitting (BF) algorithm for the nonparametric additive quantile regression (AQR) model. We establish a strong uniform consistency rate for the Bahadur representation of the BF estimators, which includes the two stage estimator of [11] as a …

cn, us (code pays fourni par la source)

Double Fairness Policy Learning: Integrating Action Fairness and Outcome Fairness in Decision-making

Zeyu Bian, Lan Wang, Chengchun Shi, Zhengling Qi

us, gb (code pays fourni par la source)

Offline Reinforcement Learning for Human-Guided Human-Machine Interaction with Private Information

Zuyue Fu, Zhengling Qi, Zhuoran Yang, Zhaoran Wang et autres

Motivated by the human-machine interaction such as recommending videos for improving customer engagement, we study human-guided human-machine interaction for decision making with private information. We model this interaction as a two-player turn-based game, where one player (Bob, a human) guides the other …

us (code pays fourni par la source)

Distributional Off-Policy Evaluation in Reinforcement Learning

Zhengling Qi, Chenjia Bai, Zhaoran Wang, Lan Wang

In the literature of reinforcement learning (RL), off-policy evaluation is mainly focused on estimating a value of a target policy given the pre-collected data generated by some behavior policy. Motivated by the recent success of distributional RL in many practical applications, we …

us, cn (code pays fourni par la source)

Combined Treatment of HCC with CTLA-4 Inhibitors and PD-1/PD-L1 Inhibitors: Mechanisms, Progress and Challenges

Lan Wang

HCC seriously threatens human health, and the treatment methods are of crucial importance. The tumor microenvironment is critical to the origin and progression of HCC, and aberrant regulation of the immune checkpoint signaling pathway is a key method by which tumor cells …

cn (code pays fourni par la source)

Private Optimal Inventory Policy Learning for Feature-Based Newsvendor with Unknown Demand

Tuoyi Zhao, Wen‐Xin Zhou, Lan Wang

The data-driven newsvendor problem with features has recently emerged as a significant area of research, driven by the proliferation of data across various sectors such as retail, supply chains, e-commerce, and healthcare. Given the sensitive nature of customer or organizational data often …

us (code pays fourni par la source)

A nonparametric doubly robust test for a continuous treatment effect

Charles R. Doss, Guangwei Weng, Lan Wang, Ira Moscovice et autres

The vast majority of literature on evaluating the significance of a treatment effect based on observational data has been confined to discrete treatments. These methods are not applicable to drawing inference for a continuous treatment, which arises in many important applications. To …

us (code pays fourni par la source)

TFRE: A Tuning-Free Robust and Efficient Approach to High-Dimensional Regression

Yunan Wu, Lan Wang

Provide functions to estimate the coefficients in high-dimensional linear regressions via a tuning-free and robust approach. The method was published in Wang, L., Peng, B., Bradic, J., Li, R. and Wu, Y. (2020), "A Tuning-free Robust and Efficient Approach to High-dimensional Regression", …

Identifying spatial heterogeneity of COVID-19 transmission clusters and their built-environment features at the neighbourhood scale

Lan Wang, Zhanzhan Hu, Kaichen Zhou, Mei‐Po Kwan

cn, hk (code pays fourni par la source)

A robust penalized-regression-based method for multivariable Mendelian randomization using GWAS summary statistics

Hongyu Zhao, Wei Jiang, Shuang Song, Liangbo Lyu et autres

Abstract Mendelian randomization (MR) is a statistical approach to inferring the causal relationships from genome-wide association studies (GWAS) by using genetic variants as instrumental variables (IVs). As IVs, the selected genetic variants should be solely associated with the exposure of interest, and …

us, cn (code pays fourni par la source)

Off-policy Evaluation in Doubly Inhomogeneous Environments

Zeyu Bian, Chengchun Shi, Zhengling Qi, Lan Wang

This work aims to study off-policy evaluation (OPE) under scenarios where two key reinforcement learning (RL) assumptions -- temporal stationarity and individual homogeneity are both violated. To handle the ``double inhomogeneities", we propose a class of latent factor models for the reward …