395 citations · 692 across the 25 of their papers we have counts for
26 papers
Self-Representation Alignment in Diffusion Models for Video Background Music Generation
Jincheng Zhang, György Fazekas, Charalampos Saitis
Diffusion models have been widely used for various generative tasks. However, recent studies have demonstrated that the internal representations learned in the diffusion models' de…
Transporting Trial Evidence Under Posterior Drift and Possible Hidden Confounding
Xilin Mao, Bosen Cui, Yuhong Yang
Randomized trials provide internally valid treatment-effect evidence, but trial participants may not represent the target population. In contrast, observational studies are often c…
Assessing Estimate of CATE from Observational Data via an RCT Study
Bosen Cui, Yuhong Yang
Conditional average treatment effects (CATEs) are increasingly estimated from observational data and used to guide policy and individualized treatment decisions. Before such estima…
Combining pre-trained models via localized model averaging
Ziwen Gao, Baihua He, Yuhong Yang
Many pre-trained models (PTMs) are available in modern applications. Because different PTMs are often trained on different datasets, their performances can vary substantially for d…
On a synergistic learning phenomenon in nonparametric domain adaptation
Ling Zhou, Yuhong Yang
Consider nonparametric domain adaptation for regression, which assumes the same conditional distribution of the response given the covariates but different marginal distributions o…
On optimality of Mallows model averaging
Jingfu Peng, Yang Li, Yuhong Yang
In the past decades, model averaging (MA) has attracted much attention as it has emerged as an alternative tool to the model selection (MS) statistical approach. Hansen [Econometri…
Minimax rates of convergence for nonparametric location-scale models
Bingxin Zhao, Yuhong Yang
This paper studies minimax rates of convergence for nonparametric location-scale models, which include mean, quantile and expectile regression settings. Under Hellinger differentia…
Multifold Cross-Validation Model Averaging for Generalized Additive Partial Linear Models
Ze Chen, Jun Liao, Wangli Xu +1
Generalized additive partial linear models (GAPLMs) are appealing for model interpretation and prediction. However, for GAPLMs, the covariates and the degree of smoothing in the no…
Variable Importance Based Interaction Modeling with an Application on Initial Spread of COVID-19 in China
Jianqiang Zhang, Ze Chen, Yuhong Yang +1
Interaction selection for linear regression models with both continuous and categorical predictors is useful in many fields of modern science, yet very challenging when the number…
Optimal integrating learning for split questionnaire design type data
Cunjie Lin, Jingfu Peng, Yichen Qin +2
In the era of data science, it is common to encounter data with different subsets of variables obtained for different cases. An example is the split questionnaire design (SQD), whi…
MinP Score Tests with an Inequality Constrained Parameter Space
Giuseppe Cavaliere, Zeng-Hua Lu, Anders Rahbek +1
Score tests have the advantage of requiring estimation alone of the model restricted by the null hypothesis, which often is much simpler than models defined under the alternative h…
To update or not to update? Delayed Nonparametric Bandits with Randomized Allocation
Sakshi Arya, Yuhong Yang
Delayed rewards problem in contextual bandits has been of interest in various practical settings. We study randomized allocation strategies and provide an understanding on how the…
On joins of a clique and a co-clique as star complements in regular graphs
Yuhong Yang, Jianfeng Wang, Qiongxiang Huang +1
In this paper we consider -regular graphs that admit the vertex set partition such that one of the induced subgraphs is the join of an -vertex clique and a -vertex co-…
Randomized Allocation with Nonparametric Estimation for Contextual Multi-Armed Bandits with Delayed Rewards
Sakshi Arya, Yuhong Yang
We study a multi-armed bandit problem with covariates in a setting where there is a possible delay in observing the rewards. Under some mild assumptions on the probability distribu…
Model Selection Techniques -- An Overview
Jie Ding, Vahid Tarokh, Yuhong Yang
In the era of big data, analysts usually explore various statistical models or machine learning methods for observed data in order to facilitate scientific discoveries or gain pred…
Combining Predictions of Auto Insurance Claims
Chenglong Ye, Lin Zhang, Mingxuan Han +3
This paper aims to better predict highly skewed auto insurance claims by combining candidate predictions. We analyze a version of the Kangaroo Auto Insurance company data and study…
High-dimensional Adaptive Minimax Sparse Estimation with Interactions
Chenglong Ye, Yuhong Yang
High-dimensional linear regression with interaction effects is broadly applied in research fields such as bioinformatics and social science. In this paper, we first investigate the…
Model Selection Confidence Sets by Likelihood Ratio Testing
Chao Zheng, Davide Ferrari, Yuhong Yang
The traditional activity of model selection aims at discovering a single model superior to other candidate models. In the presence of pronounced noise, however, multiple models are…
Performance Assessment of High-dimensional Variable Identification
Yanjia Yu, Yi Yang, Yuhong Yang
Since model selection is ubiquitous in data analysis, reproducibility of statistical results demands a serious evaluation of reliability of the employed model selection method, no…
Sparsity Oriented Importance Learning for High-dimensional Linear Regression
Chenglong Ye, Yi Yang, Yuhong Yang
With now well-recognized non-negligible model selection uncertainty, data analysts should no longer be satisfied with the output of a single final model from a model selection proc…
Forecast Combination Under Heavy-Tailed Errors
Gang Cheng, Sicong Wang, Yuhong Yang
Forecast combination has been proven to be a very important technique to obtain accurate predictions. In many applications, forecast errors exhibit heavy tail behaviors for various…
Bridging AIC and BIC: a new criterion for autoregression
Jie Ding, Vahid Tarokh, Yuhong Yang
We introduce a new criterion to determine the order of an autoregressive model fitted to time series data. It has the benefits of the two well-known model selection techniques, the…
On the Forecast Combination Puzzle
Wei Qian, Craig A. Rolling, Gang Cheng +1
It is often reported in forecast combination literature that a simple average of candidate forecasts is more robust than sophisticated combining methods. This phenomenon is usually…
Parametric or nonparametric? A parametricness index for model selection
Wei Liu, Yuhong Yang
In model selection literature, two classes of criteria perform well asymptotically in different situations: Bayesian information criterion (BIC) (as a representative) is consistent…