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Exploiting Local Feature Patterns for Unsupervised Domain Adaptation
Jun Wen, Risheng Liu, Nenggan Zheng +3
Unsupervised domain adaptation methods aim to alleviate performance degradation caused by domain-shift by learning domain-invariant representations. Existing deep domain adaptation…
A Theoretically Guaranteed Deep Optimization Framework for Robust Compressive Sensing MRI
Risheng Liu, Yuxi Zhang, Shichao Cheng +2
Magnetic Resonance Imaging (MRI) is one of the most dynamic and safe imaging techniques available for clinical applications. However, the rather slow speed of MRI acquisitions limi…
Task Embedded Coordinate Update: A Realizable Framework for Multivariate Non-convex Optimization
Yiyang Wang, Risheng Liu, Long Ma +1
We in this paper propose a realizable framework TECU, which embeds task-specific strategies into update schemes of coordinate descent, for optimizing multivariate non-convex proble…
Learning Converged Propagations with Deep Prior Ensemble for Image Enhancement
Risheng Liu, Long Ma, Yiyang Wang +1
Enhancing visual qualities of images plays very important roles in various vision and learning applications. In the past few years, both knowledge-driven maximum a posterior (MAP)…
On the Convergence of Learning-based Iterative Methods for Nonconvex Inverse Problems
Risheng Liu, Shichao Cheng, Yi He +3
Numerous tasks at the core of statistics, learning and vision areas are specific cases of ill-posed inverse problems. Recently, learning-based (e.g., deep) iterative methods have b…
Learning Collaborative Generation Correction Modules for Blind Image Deblurring and Beyond
Risheng Liu, Yi He, Shichao Cheng +2
Blind image deblurring plays a very important role in many vision and multimedia applications. Most existing works tend to introduce complex priors to estimate the sharp image stru…
Toward Designing Convergent Deep Operator Splitting Methods for Task-specific Nonconvex Optimization
Risheng Liu, Shichao Cheng, Yi He +2
Operator splitting methods have been successfully used in computational sciences, statistics, learning and vision areas to reduce complex problems into a series of simpler subprobl…