R
Risheng Liu
Researcher at Dalian University of Technology
Publications - 250
Citations - 5184
Risheng Liu is an academic researcher from Dalian University of Technology. The author has contributed to research in topics: Computer science & Image processing. The author has an hindex of 26, co-authored 200 publications receiving 3465 citations. Previous affiliations of Risheng Liu include Hangzhou Normal University & Hong Kong Polytechnic University.
Papers
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Proceedings Article
Linearized Alternating Direction Method with Adaptive Penalty for Low-Rank Representation
TL;DR: A linearized ADM (LADM) method is proposed by linearizing the quadratic penalty term and adding a proximal term when solving the sub-problems, allowing the penalty to change adaptively according to a novel update rule.
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Linearized Alternating Direction Method with Adaptive Penalty for Low-Rank Representation
TL;DR: In this paper, a linearized alternating direction method with adaptive penalty (LADMAP) method was proposed to solve the problem of low-rank representation (LRR) for convex programs.
Journal ArticleDOI
Linearized alternating direction method with parallel splitting and adaptive penalty for separable convex programs in machine learning
Zhouchen Lin,Risheng Liu,Huan Li +2 more
TL;DR: This paper proposes LADM with parallel splitting and adaptive penalty (LADMPSAP) to solve multi-block separable convex programs efficiently and proposes a simple optimality measure and reveals the convergence rate of LADmPSAP in an ergodic sense.
Proceedings ArticleDOI
Fixed-rank representation for unsupervised visual learning
TL;DR: In this article, a fixed-rank representation (FRR) framework is proposed to reveal the structure of multiple subspaces in closed-form when the data is noiseless.
Proceedings ArticleDOI
Adaptive Partial Differential Equation Learning for Visual Saliency Detection
TL;DR: Experimental results on various challenging image sets show the superiority of the proposed learning-based PDEs for visual saliency detection, which are based on a novel framework for adaptively learning a PDE system from an image for visualSaliency detection.