576 citations · 1.1k across the 42 of their papers we have counts for
42 papers
Muon-C: Operator-Aligned Muon for Convolutional Kernels
Jiaxin Qing, Lexin Li
Muon replaces matrix momentum with an approximately orthogonal polar direction, but its geometry depends on the matrix representation. For convolution, standard unfolding describes…
Channel-Preserving Representation Alignment for EEG-to-Music Reconstruction
Jiaxin Qing, Junwei Lu, Lexin Li
Reconstructing naturalistic music from EEG requires extracting music-specific information from weak signals distributed across electrodes. Existing spectrogram regression and diffu…
Context-aware tokenization for Cross-subject Emotion Decoding from EEG
Jiaxin Qing, Lexin Li
In cross-subject EEG emotion decoding, neighboring windows can inform the representation of a target window, but they contain both background variation and sustained task signals.…
Synthetic Oversampling: Theory and A Practical Approach Using LLMs to Address Data Imbalance
Ryumei Nakada, Yichen Xu, Lexin Li +1
Imbalanced classification and spurious correlation are common challenges in data science and machine learning. Both issues are linked to data imbalance, with certain groups of data…
Estimation and Inference for High-dimensional Multi-response Growth Curve Model
Xin Zhou, Yin Xia, Lexin Li
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 u…
Multivariate Dynamic Mediation Analysis under a Reinforcement Learning Framework
Lan Luo, Chengchun Shi, Jitao Wang +2
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 a…
Testing for the Markov Property in Time Series via Deep Conditional Generative Learning
Yunzhe Zhou, Chengchun Shi, Lexin Li +1
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 pa…
High-dimensional Response Growth Curve Modeling for Longitudinal Neuroimaging Analysis
Lu Wang, Xiang Lyu, Zhengwu Zhang +1
There is increasing interest in modeling high-dimensional longitudinal outcomes in applications such as developmental neuroimaging research. Growth curve model offers a useful tool…
Optimizing Pessimism in Dynamic Treatment Regimes: A Bayesian Learning Approach
Yunzhe Zhou, Zhengling Qi, Chengchun Shi +1
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…
Sliced Inverse Regression in Metric Spaces
Joni Virta, Kuang-Yao Lee, Lexin Li
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…
NAPA: Neighborhood-Assisted and Posterior-Adjusted Two-sample Inference
Li Ma, Yin Xia, Lexin Li
Two-sample multiple testing problems of sparse spatial data are frequently arising in a variety of scientific applications. In this article, we develop a novel neighborhood-assiste…
Post-Regularization Confidence Bands for Ordinary Differential Equations
Xiaowu Dai, Lexin Li
Ordinary differential equation (ODE) is an important tool to study the dynamics of a system of biological and physical processes. A central question in ODE modeling is to infer the…
Testing Directed Acyclic Graph via Structural, Supervised and Generative Adversarial Learning
Chengchun Shi, Yunzhe Zhou, Lexin Li
In this article, we propose a new hypothesis testing method for directed acyclic graph (DAG). While there is a rich class of DAG estimation methods, there is a relative paucity of…
Nonparametric Trace Regression in High Dimensions via Sign Series Representation
Chanwoo Lee, Lexin Li, Hao Helen Zhang +1
Learning of matrix-valued data has recently surged in a range of scientific and business applications. Trace regression is a widely used method to model effects of matrix predictor…
Kernel Knockoffs Selection for Nonparametric Additive Models
Xiaowu Dai, Xiang Lyu, Lexin Li
Thanks to its fine balance between model flexibility and interpretability, the nonparametric additive model has been widely used, and variable selection for this type of model has…
Multimodal Data Integration via Mediation Analysis with High-Dimensional Exposures and Mediators
Yi Zhao, Lexin Li
Motivated by an imaging proteomics study for Alzheimer's disease (AD), in this article, we propose a mediation analysis approach with high-dimensional exposures and high-dimensiona…
Orthogonalized Kernel Debiased Machine Learning for Multimodal Data Analysis
Xiaowu Dai, Lexin Li
Multimodal imaging has transformed neuroscience research. While it presents unprecedented opportunities, it also imposes serious challenges. Particularly, it is difficult to combin…
Statistical Inference for High-Dimensional Vector Autoregression with Measurement Error
Xiang Lyu, Jian Kang, Lexin Li
High-dimensional vector autoregression with measurement error is frequently encountered in a large variety of scientific and business applications. In this article, we study statis…
Generalized Liquid Association Analysis for Multimodal Data Integration
Lexin Li, Jing Zeng, Xin Zhang
Multimodal data are now prevailing in scientific research. A central question in multimodal integrative analysis is to understand how two data modalities associate and interact wit…
Kernel Ordinary Differential Equations
Xiaowu Dai, Lexin Li
Ordinary differential equation (ODE) is widely used in modeling biological and physical processes in science. In this article, we propose a new reproducing kernel-based approach fo…
Image Response Regression via Deep Neural Networks
Daiwei Zhang, Lexin Li, Chandra Sripada +1
Delineating the associations between images and a vector of covariates is of central interest in medical imaging studies. To tackle this problem of image response regression, we pr…
Testing Mediation Effects Using Logic of Boolean Matrices
Chengchun Shi, Lexin Li
Mediation analysis is becoming an increasingly important tool in scientific studies. A central question in high-dimensional mediation analysis is to infer the significance of indiv…
Partially Observed Dynamic Tensor Response Regression
Jie Zhou, Will Wei Sun, Jingfei Zhang +1
In modern data science, dynamic tensor data is prevailing in numerous applications. An important task is to characterize the relationship between such dynamic tensor and external c…
Multivariate Temporal Point Process Regression
Xiwei Tang, Lexin Li
Point process modeling is gaining increasing attention, as point process type data are emerging in numerous scientific applications. In this article, motivated by a neuronal spike…