1 citations · 1 across the 9 of their papers we have counts for
9 papers
Beyond Cross-Validation: Adaptive Parameter Selection for Kernel-Based Gradient Descents
Xiaotong Liu, Yunwen Lei, Xiangyu Chang +1
This paper proposes a novel parameter selection strategy for kernel-based gradient descent (KGD) algorithms, integrating bias-variance analysis with the splitting method. We introd…
Towards Accurate and Interpretable Time-series Forecasting: A Polynomial Learning Approach
Bo Liu, Shao-Bo Lin, Changmiao Wang +1
Time series forecasting enables early warning and has driven asset performance management from traditional planned maintenance to predictive maintenance. However, the lack of inter…
Two-Stage Data Synthesization: A Statistics-Driven Restricted Trade-off between Privacy and Prediction
Xiaotong Liu, Shao-Bo Lin, Jun Fan +1
Synthetic data have gained increasing attention across various domains, with a growing emphasis on their performance in downstream prediction tasks. However, most existing synthesi…
Transcending Sparse Measurement Limits: Operator-Learning-Driven Data Super-Resolution for Inverse Source Problem
Guanyu Pan, Jianing Zhou, Xiaotong Liu +2
Inverse source localization from Helmholtz boundary data collected over a narrow aperture is highly ill-posed and severely undersampled, undermining classical solvers (e.g., the Di…
Striking the Perfect Balance: Preserving Privacy While Boosting Utility in Collaborative Medical Prediction Platforms
Shao-Bo Lin, Xiaotong Liu, Yao Wang
Online collaborative medical prediction platforms offer convenience and real-time feedback by leveraging massive electronic health records. However, growing concerns about privacy…
Reconstruction with prior support information and non-Gaussian constraints
Xiaotong Liu, Yiyu Liang
In this study, we introduce a novel model, termed the Weighted Basis Pursuit Dequantization (-BPDQ), which incorporates prior support information by assigning weights on the…
A signal recovery guarantee with Restricted Isometry Property and Null Space Property for weighted minimization
Xiaotong Liu, Yiyu Liang
Signal reconstruction is a crucial aspect of compressive sensing. In weighted cases, there are two common types of weights. In order to establish a unified framework for handling v…
Weighted Spectral Filters for Kernel Interpolation on Spheres: Estimates of Prediction Accuracy for Noisy Data
Xiaotong Liu, Jinxin Wang, Di Wang +1
Spherical radial-basis-based kernel interpolation abounds in image sciences including geophysical image reconstruction, climate trends description and image rendering due to its ex…
Adaptive Distributed Kernel Ridge Regression: A Feasible Distributed Learning Scheme for Data Silos
Di Wang, Xiaotong Liu, Shao-Bo Lin +1
Data silos, mainly caused by privacy and interoperability, significantly constrain collaborations among different organizations with similar data for the same purpose. Distributed…