Proximal gradient methods for general smooth graph total variation model in unsupervised learning
From MaRDI portal
Publication:2674267
DOI10.1007/s10915-022-01954-0OpenAlexW4292707226MaRDI QIDQ2674267
Publication date: 22 September 2022
Published in: Journal of Scientific Computing (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s10915-022-01954-0
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Nonlinear total variation based noise removal algorithms
- A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems
- FASTA
- Proximal alternating linearized minimization for nonconvex and nonsmooth problems
- Numerical approximations for the molecular beam epitaxial growth model based on the invariant energy quadratization method
- An effective region force for some variational models for learning and clustering
- \(\Gamma\)-convergence of graph Ginzburg-Landau functionals
- Convergence of descent methods for semi-algebraic and tame problems: proximal algorithms, forward-backward splitting, and regularized Gauss-Seidel methods
- Image colorization by using graph bi-Laplacian
- The gradient projection algorithm for smooth sets and functions in nonconvex case
- Nonlocal regularized CNN for image segmentation
- Energy and entropy preserving numerical approximations of thermodynamically consistent crystal growth models
- Adaptive restart for accelerated gradient schemes
- Sparse representation on graphs by tight wavelet frames and applications
- Splitting Methods in Communication, Imaging, Science, and Engineering
- An MBO Scheme on Graphs for Classification and Image Processing
- Linear Convergence of Proximal Gradient Algorithm with Extrapolation for a Class of Nonconvex Nonsmooth Minimization Problems
- Generalizing Diffuse Interface Methods on Graphs: Nonsmooth Potentials and Hypergraphs
- Simplified Energy Landscape for Modularity Using Total Variation
- A Block Nonlocal TV Method for Image Restoration
- Diffuse Interface Models on Graphs for Classification of High Dimensional Data
- Overlapping Domain Decomposition Methods for Ptychographic Imaging
- A New Class of Efficient and Robust Energy Stable Schemes for Gradient Flows
- Some Facts About Operator-Splitting and Alternating Direction Methods
- A Method Based on Total Variation for Network Modularity Optimization Using the MBO Scheme
This page was built for publication: Proximal gradient methods for general smooth graph total variation model in unsupervised learning