Zobrazeno 1 - 10
of 420
pro vyhledávání: '"Li Lexin"'
Estimating treatment effects from observational data is of central interest across numerous application domains. Individual treatment effect offers the most granular measure of treatment effect on an individual level, and is the most useful to facili
Externí odkaz:
http://arxiv.org/abs/2408.01582
Imbalanced data and spurious correlations are common challenges in machine learning and data science. Oversampling, which artificially increases the number of instances in the underrepresented classes, has been widely adopted to tackle these challeng
Externí odkaz:
http://arxiv.org/abs/2406.03628
A growth curve model (GCM) aims to characterize how an outcome variable evolves, develops and grows as a function of time, along with other predictors. It provides a particularly useful framework to model growth trend in longitudinal data. However, t
Externí odkaz:
http://arxiv.org/abs/2312.16769
Mediation analysis is an important analytic tool commonly used in a broad range of scientific applications. In this article, we study the problem of mediation analysis when there are multivariate and conditionally dependent mediators, and when the va
Externí odkaz:
http://arxiv.org/abs/2310.16203
The Markov property is widely imposed in analysis of time series data. Correspondingly, testing the Markov property, and relatedly, inferring the order of a Markov model, are of paramount importance. In this article, we propose a nonparametric test f
Externí odkaz:
http://arxiv.org/abs/2305.19244
There is increasing interest in modeling high-dimensional longitudinal outcomes in applications such as developmental neuroimaging research. Growth curve model offers a useful tool to capture both the mean growth pattern across individuals, as well a
Externí odkaz:
http://arxiv.org/abs/2305.15751
A brain-computer interface (BCI) is a technology that enables direct communication between the brain and an external device or computer system. It allows individuals to interact with the device using only their thoughts, and holds immense potential f
Externí odkaz:
http://arxiv.org/abs/2305.11908
In this article, we propose a novel pessimism-based Bayesian learning method for optimal dynamic treatment regimes in the offline setting. When the coverage condition does not hold, which is common for offline data, the existing solutions would produ
Externí odkaz:
http://arxiv.org/abs/2210.14420
In this article, we propose a general nonlinear sufficient dimension reduction (SDR) framework when both the predictor and response lie in some general metric spaces. We construct reproducing kernel Hilbert spaces whose kernels are fully determined b
Externí odkaz:
http://arxiv.org/abs/2206.11511
Publikováno v:
In Journal of Cleaner Production 20 October 2024 477
