Wenwu Gong's Projects
Paper "Accurate Regularized Tucker Decomposition for Image Restoration"๏ผin APM 2023
Paper "Guaranteed Tensor Recovery Fused Low-rankness and Smoothness"๏ผ published in TPAMI 2023
Implementation of Hybrid ISTA: Unfolding ISTA With Convergence Guarantees Using Free-Form Deep Neural Networks
Tuning-free Plug-and-Play Proximal Algorithm for Inverse Imaging Problems (ICML 2020 Award Paper & JMLR 2022)
In the Data Science and Engineering program, engineering professionals combine the skills of software programmer, database manager, and statistician to create mathematical models of the data, identify trends/deviations, then present them in effective visual ways that can be understood by others. Data scientists unlock new sources of economic value, provide fresh insights into science, and inform decision makers by analyzing large, diverse, complex, longitudinal, and distributed data sets generated from instruments, sensors, internet transactions, email, video, and other digital sources. Students entering the MAS program for a degree in Data Science and Engineering will undertake courses in programming, analysis, and applications management and visualization. This program requires three foundational courses, four core courses, and two electives totaling thirty-four units, plus a capstone team project course of four units, for a total of thirty-eight units.
ELRSTD Conference paper in ICASSP 2024.
Config files for my GitHub profile.
HomePage
HW
ESI_paper collection on LRTL
LSPTD Conference paper in ITSC 2023.
machine learning and deep learning tutorials, articles and other resources
A Survey on Nonconvex Regularization Based Sparse and Low-Rank Recovery in Signal Processing, Statistics, and Machine Learning
Matlab codes for feature learning
Low-Rank and Sparse Tools for Background Modeling and Subtraction in Videos
tensor-tensor product toolbox
Machine learning for transportation data imputation and prediction.
SARIMA_Intervention_POLS
Paper "Spatiotemporal regularized Tucker decomposition approach for traffic data imputation"๏ผin arXiv 2023
List of papers, code and experiments using deep learning for time series forecasting
Introduction to Tensor Decompositions and their Applications
Dynamic Risk Assessment of Compound Hazards_NHESS