Zhouchen Lin

Zhouchen Lin's AcademicInfluence.com Rankings

Zhouchen Lin

Computer Science

#4426

World Rank

#4662

Historical Rank

Machine Learning

#859

World Rank

#871

Historical Rank

Database

#1642

World Rank

#1722

Historical Rank

computer-science Degrees

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Computer Science

Zhouchen Lin's Degrees

PhD Computer Science Peking University
Masters Computer Science Peking University
Bachelors Computer Science Peking University

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Zhouchen Lin's Published Works

Number of citations in a given year to any of this author's works

Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author

Published Works

Robust Recovery of Subspace Structures by Low-Rank Representation (2010) (2749)
The Augmented Lagrange Multiplier Method for Exact Recovery of Corrupted Low-Rank Matrices (2010) (2565)
Robust Subspace Segmentation by Low-Rank Representation (2010) (1545)
Linearized Alternating Direction Method with Adaptive Penalty for Low-Rank Representation (2011) (1059)
Fast Convex Optimization Algorithms for Exact Recovery of a Corrupted Low-Rank Matrix (2009) (506)
Fundamental limits of reconstruction-based superresolution algorithms under local translation (2004) (452)
Recurrent Squeeze-and-Excitation Context Aggregation Net for Single Image Deraining (2018) (448)
Tensor Robust Principal Component Analysis with a New Tensor Nuclear Norm (2018) (442)
SPIDER: Near-Optimal Non-Convex Optimization via Stochastic Path Integrated Differential Estimator (2018) (414)
Tensor Robust Principal Component Analysis: Exact Recovery of Corrupted Low-Rank Tensors via Convex Optimization (2016) (399)
Fast, automatic and fine-grained tampered JPEG image detection via DCT coefficient analysis (2009) (356)
Expectation-Maximization Attention Networks for Semantic Segmentation (2019) (339)
Accelerated Proximal Gradient Methods for Nonconvex Programming (2015) (339)
Laplacian Regularized Low-Rank Representation and Its Applications (2016) (328)
Relay Backpropagation for Effective Learning of Deep Convolutional Neural Networks (2015) (315)
Non-negative low rank and sparse graph for semi-supervised learning (2012) (309)
Generalized Nonconvex Nonsmooth Low-Rank Minimization (2014) (248)
Subspace Clustering by Block Diagonal Representation (2018) (241)
Smooth Representation Clustering (2014) (233)
Nonconvex Nonsmooth Low Rank Minimization via Iteratively Reweighted Nuclear Norm (2015) (219)
Robust Estimation of 3D Human Poses from a Single Image (2014) (202)
Correlation Adaptive Subspace Segmentation by Trace Lasso (2013) (189)
Detecting Doctored JPEG Images Via DCT Coefficient Analysis (2006) (181)
Linearized alternating direction method with parallel splitting and adaptive penalty for separable convex programs in machine learning (2013) (179)
Fast algorithms for recovering a corrupted low-rank matrix (2009) (178)
On the Applications of Robust PCA in Image and Video Processing (2018) (176)
Robust Subspace Segmentation with Block-Diagonal Prior (2014) (176)
Tensor Factorization for Low-Rank Tensor Completion (2018) (175)
Generalized Singular Value Thresholding (2014) (164)
Multi-Stage Self-Supervised Learning for Graph Convolutional Networks (2019) (157)
Fixed-rank representation for unsupervised visual learning (2012) (147)
Essential Tensor Learning for Multi-View Spectral Clustering (2018) (144)
Detecting doctored images using camera response normality and consistency (2005) (143)
Adaptive Partial Differential Equation Learning for Visual Saliency Detection (2014) (131)
Improving Semantic Segmentation via Decoupled Body and Edge Supervision (2020) (127)
Smoothed Low Rank and Sparse Matrix Recovery by Iteratively Reweighted Least Squares Minimization (2014) (118)
Dual Graph Regularized Latent Low-Rank Representation for Subspace Clustering (2015) (117)
Convolutional Neural Networks with Alternately Updated Clique (2018) (117)
A Unified Alternating Direction Method of Multipliers by Majorization Minimization (2016) (111)
A comparison of typical ℓp minimization algorithms (2013) (109)
A Generalized Accelerated Proximal Gradient Approach for Total-Variation-Based Image Restoration (2011) (107)
Invertible Image Rescaling (2020) (107)
Convex Sparse Spectral Clustering: Single-View to Multi-View (2015) (105)
Spatial Pyramid Based Graph Reasoning for Semantic Segmentation (2020) (103)
Alternating Multi-bit Quantization for Recurrent Neural Networks (2018) (101)
Bilinear Factor Matrix Norm Minimization for Robust PCA: Algorithms and Applications (2018) (101)
The multiscale competitive code via sparse representation for palmprint verification (2010) (98)
Deep Comprehensive Correlation Mining for Image Clustering (2019) (97)
Self-Supervised Convolutional Subspace Clustering Network (2019) (97)
Emotion Recognition from Arbitrary View Facial Images (2010) (94)
Correntropy Induced L2 Graph for Robust Subspace Clustering (2013) (91)
Kernel Nyström method for light transport (2009) (91)
Investigating Bi-Level Optimization for Learning and Vision From a Unified Perspective: A Survey and Beyond (2021) (90)
Constructing a Nonnegative Low-Rank and Sparse Graph With Data-Adaptive Features (2014) (88)
Sharp Analysis for Nonconvex SGD Escaping from Saddle Points (2019) (85)
A Geometric Analysis of Light Field Rendering (2004) (84)
Modeling and rendering of heterogeneous translucent materials using the diffusion equation (2008) (84)
Neural Multimodal Cooperative Learning Toward Micro-Video Understanding (2020) (83)
Robust Kernel Estimation with Outliers Handling for Image Deblurring (2016) (82)
A novel approach to expression recognition from non-frontal face images (2009) (78)
Contextual Distance for Data Perception (2007) (73)
Robust nuclear norm regularized regression for face recognition with occlusion (2015) (72)
Exact Low Tubal Rank Tensor Recovery from Gaussian Measurements (2018) (70)
L1-Norm Kernel Discriminant Analysis Via Bayes Error Bound Optimization for Robust Feature Extraction (2014) (68)
Robust latent low rank representation for subspace clustering (2014) (67)
Limits of Learning-Based Superresolution Algorithms (2007) (66)
Integrated Low-Rank-Based Discriminative Feature Learning for Recognition (2016) (62)
Optimized Projections for Compressed Sensing via Direct Mutual Coherence Minimization (2015) (60)
On the number of samples needed in light field rendering with constant-depth assumption (2000) (58)
Linearized Alternating Direction Method with Adaptive Penalty and Warm Starts for Fast Solving Transform Invariant Low-Rank Textures (2012) (58)
Analysis and Improvement of Low Rank Representation for Subspace segmentation (2010) (58)
Is Attention Better Than Matrix Decomposition? (2021) (58)
Label Information Guided Graph Construction for Semi-Supervised Learning (2017) (58)
On the Convergence of Learning-Based Iterative Methods for Nonconvex Inverse Problems (2018) (57)
Linear Laplacian Discrimination for Feature Extraction (2007) (56)
Laplacian PCA and Its Applications (2007) (56)
Joint Sub-bands Learning with Clique Structures for Wavelet Domain Super-Resolution (2018) (55)
Penrose Pixels Super-Resolution in the Detector Layout Domain (2007) (55)
Tensor Low-Rank Representation for Data Recovery and Clustering (2019) (55)
Learning PDEs for Image Restoration via Optimal Control (2010) (51)
t-Schatten-$p$ Norm for Low-Rank Tensor Recovery (2018) (51)
Subspace clustering by Mixture of Gaussian Regression (2015) (51)
Differentiable Linearized ADMM (2019) (51)
Tensor LRR and Sparse Coding-Based Subspace Clustering (2016) (51)
A Geometric Method for Optimal Design of Color Filter Arrays (2011) (49)
Multi-Level Discriminative Dictionary Learning With Application to Large Scale Image Classification (2015) (49)
Relighting with the Reflected Irradiance Field: Representation, Sampling and Reconstruction (2001) (48)
SOGNet: Scene Overlap Graph Network for Panoptic Segmentation (2019) (47)
AdaGCN: Adaboosting Graph Convolutional Networks into Deep Models (2019) (47)
Radon Representation-Based Feature Descriptor for Texture Classification (2009) (46)
Robust Matrix Factorization by Majorization Minimization (2018) (43)
ISTA-NAS: Efficient and Consistent Neural Architecture Search by Sparse Coding (2020) (41)
Learning to Diffuse: A New Perspective to Design PDEs for Visual Analysis (2016) (40)
Unified Graph and Low-Rank Tensor Learning for Multi-View Clustering (2020) (38)
A Unified Convex Surrogate for the Schatten-p Norm (2016) (38)
Solving Principal Component Pursuit in Linear Time via $l_1$ Filtering (2011) (38)
Multi-output regression on the output manifold (2009) (37)
Unsupervised Object Segmentation with a Hybrid Graph Model (HGM) (2010) (37)
An anisotropic diffusion PDE for noise reduction and thin edge preservation (1999) (35)
Joint Latent Subspace Learning and Regression for Cross-Modal Retrieval (2017) (35)
Learning Semi-Supervised Representation Towards a Unified Optimization Framework for Semi-Supervised Learning (2015) (34)
Bilevel Model-Based Discriminative Dictionary Learning for Recognition (2017) (34)
Multiple Models Fusion for Emotion Recognition in the Wild (2015) (33)
Robust 3D Human Pose Estimation from Single Images or Video Sequences (2019) (32)
Real-time rendering of realistic rain (2006) (32)
Exact Recoverability of Robust PCA via Outlier Pursuit with Tight Recovery Bounds (2015) (32)
Leveraged Weighted Loss for Partial Label Learning (2021) (31)
Accelerated Alternating Direction Method of Multipliers: An Optimal O(1 / K) Nonergodic Analysis (2016) (31)
A Sharp Convergence Rate Analysis for Distributed Accelerated Gradient Methods (2018) (31)
Robust Low-Rank Regularized Regression for Face Recognition with Occlusion (2014) (30)
Towards Improving the Consistency, Efficiency, and Flexibility of Differentiable Neural Architecture Search (2021) (30)
Locality-preserving low-rank representation for graph construction from nonlinear manifolds (2016) (30)
Lifted Proximal Operator Machines (2018) (30)
Tensor linear Laplacian discrimination (TLLD) for feature extraction (2009) (30)
PointFlow: Flowing Semantics Through Points for Aerial Image Segmentation (2021) (30)
A Counterexample for the Validity of Using Nuclear Norm as a Convex Surrogate of Rank (2013) (29)
Relations Among Some Low-Rank Subspace Recovery Models (2014) (29)
Two-weight and three-weight linear codes based on Weil sums (2016) (29)
Graph Contrastive Clustering (2021) (29)
Optimization Algorithm Inspired Deep Neural Network Structure Design (2018) (28)
Nonconvex Nonsmooth Low-Rank Minimization via Iteratively Reweighted Nuclear Norm. (2015) (28)
PDO-eConvs: Partial Differential Operator Based Equivariant Convolutions (2020) (27)
Feature learning via partial differential equation with applications to face recognition (2017) (27)
Decentralized Accelerated Gradient Methods With Increasing Penalty Parameters (2018) (27)
Revisiting EXTRA for Smooth Distributed Optimization (2020) (27)
Linear time Principal Component Pursuit and its extensions using ℓ1 filtering (2014) (27)
Dissecting the Diffusion Process in Linear Graph Convolutional Networks (2021) (26)
Feature extraction by learning Lorentzian metric tensor and its extensions (2010) (26)
Toward designing intelligent PDEs for computer vision: An optimal control approach (2011) (26)
Penrose Pixels for Super-Resolution (2011) (26)
Transformation invariant subspace clustering (2016) (24)
Chaos is a Ladder: A New Theoretical Understanding of Contrastive Learning via Augmentation Overlap (2022) (24)
Low-Rank Models in Visual Analysis: Theories, Algorithms, and Applications (2017) (24)
A robust hybrid method for text detection in natural scenes by learning-based partial differential equations (2015) (24)
Dictionary learning with structured noise (2018) (24)
Training High-Performance Low-Latency Spiking Neural Networks by Differentiation on Spike Representation (2022) (24)
On Training Implicit Models (2021) (23)
On the fundamental limits of reconstruction-based super-resolution algorithms (2001) (23)
A review on low-rank models in data analysis (2016) (22)
Accelerated Gradient Tracking over Time-varying Graphs for Decentralized Optimization (2021) (22)
Completing Low-Rank Matrices With Corrupted Samples From Few Coefficients in General Basis (2015) (21)
Automatic Design of Color Filter Arrays in the Frequency Domain (2016) (21)
A Block Lanczos with Warm Start Technique for Accelerating Nuclear Norm Minimization Algorithms (2010) (20)
Virtual Adversarial Training on Graph Convolutional Networks in Node Classification (2019) (20)
Fast gradient vector flow computation based on augmented Lagrangian method (2013) (20)
Locality-constrained linear coding based bi-layer model for multi-view facial expression recognition (2017) (19)
Implicit Euler Skip Connections: Enhancing Adversarial Robustness via Numerical Stability (2020) (19)
ADA-Tucker: Compressing deep neural networks via adaptive dimension adjustment tucker decomposition (2019) (19)
Classification via Minimum Incremental Coding Length (MICL) (2007) (19)
Proximal Iteratively Reweighted Algorithm with Multiple Splitting for Nonconvex Sparsity Optimization (2014) (18)
Learning Deep Sparse Regularizers With Applications to Multi-View Clustering and Semi-Supervised Classification (2021) (18)
Convergence Rates Analysis of The Quadratic Penalty Method and Its Applications to Decentralized Distributed Optimization (2017) (18)
Towards Understanding Adversarial Examples Systematically: Exploring Data Size, Task and Model Factors (2019) (18)
Fast Proximal Linearized Alternating Direction Method of Multiplier with Parallel Splitting (2015) (18)
Penrose Demosaicking (2015) (17)
Residual Relaxation for Multi-view Representation Learning (2021) (17)
Optimal Accelerated Variance Reduced EXTRA and DIGing for Strongly Convex and Smooth Decentralized Optimization (2020) (17)
High Resolution Animated Scenes from Stills (2007) (17)
Training Feedback Spiking Neural Networks by Implicit Differentiation on the Equilibrium State (2021) (17)
Color Filter Arrays : Representation and Analysis (2008) (17)
Learning Markov random walks for robust subspace clustering and estimation (2014) (17)
Accelerated Optimization for Machine Learning: First-Order Algorithms (2020) (17)
Accelerated First-Order Optimization Algorithms for Machine Learning (2020) (17)
Learning Partial Differential Equations for Computer Vision ∗ (2010) (17)
Enhancing the Robustness of Deep Neural Networks by Boundary Conditional GAN (2019) (16)
Dynamical System Inspired Adaptive Time Stepping Controller for Residual Network Families (2019) (16)
Gauge Equivariant Transformer (2021) (16)
Learning Semi-Riemannian Metrics for Semisupervised Feature Extraction (2011) (16)
Analysis on Rate-Distortion Performance of Compressive Sensing for Binary Sparse Source (2009) (16)
A Regularized Approach for Geodesic-Based Semisupervised Multimanifold Learning (2014) (15)
Low-Rank Matrix Recovery Via Robust Outlier Estimation (2018) (14)
The Shape Interaction Matrix-Based Affine Invariant Mismatch Removal for Partial-Duplicate Image Search (2017) (13)
Nonconvex Sparse Spectral Clustering by Alternating Direction Method of Multipliers and Its Convergence Analysis (2017) (13)
Accelerating Iterations Involving Eigenvalue or Singular Value Decomposition by Block Lanczos with Warm Start (2010) (13)
Classification via semi-Riemannian spaces (2008) (13)
Towards Efficient Scene Understanding via Squeeze Reasoning (2020) (13)
Efficient tree-structured SfM by RANSAC generalized Procrustes analysis (2017) (13)
Classification via Minimum Incremental Coding Length (2009) (13)
Multi-view common space learning for emotion recognition in the wild (2016) (13)
Optimized Color Filter Arrays for Sparse Representation-Based Demosaicking (2017) (13)
Accelerated Variance Reduction Stochastic ADMM for Large-Scale Machine Learning (2020) (12)
Subspace Clustering Under Complex Noise (2019) (12)
Automatic Design of High-Sensitivity Color Filter Arrays With Panchromatic Pixels (2017) (12)
Color Filter Arrays: A Design Methodology (2008) (12)
Accelerating Asynchronous Algorithms for Convex Optimization by Momentum Compensation (2018) (12)
Tensor Sparse and Low-Rank based Submodule Clustering Method for Multi-way Data (2016) (12)
Provable accelerated gradient method for nonconvex low rank optimization (2017) (12)
Do We Really Need a Learnable Classifier at the End of Deep Neural Network? (2022) (12)
Parallel Asynchronous Stochastic Variance Reduction for Nonconvex Optimization (2017) (12)
Relaxed Majorization-Minimization for Non-Smooth and Non-Convex Optimization (2015) (11)
A Hybrid Graph Model for Unsupervised Object Segmentation (2007) (11)
Some Software Packages for Partial SVD Computation (2011) (11)
Designing Partial Differential Equations for Image Processing by Combining Differential Invariants (2009) (11)
Rectification of Optical Characters as Transform Invariant Low-Rank Textures (2013) (10)
Table detection in online ink notes (2006) (10)
Training much deeper spiking neural networks with a small number of time-steps (2022) (10)
Transform invariant text extraction (2014) (10)
Faster and Non-ergodic O(1/K) Stochastic Alternating Direction Method of Multipliers (2017) (10)
Variance Reduced EXTRA and DIGing and Their Optimal Acceleration for Strongly Convex Decentralized Optimization (2020) (10)
Efficient Equivariant Network (2021) (10)
Response to the Comments on "Fundamental Limits of Reconstruction-Based Superresolution Algorithms under Local Translation' (2006) (9)
Tensor Q-rank: new data dependent definition of tensor rank (2019) (9)
Joint Dictionary Learning and Semantic Constrained Latent Subspace Projection for Cross-Modal Retrieval (2018) (9)
Geodesic Based Semi-supervised Multi-manifold Feature Extraction (2012) (9)
R ^2 2 -Net: Recurrent and Recursive Network for Sparse-View CT Artifacts Removal (2019) (9)
Learning Deep Convolutional Neural Networks for Places2 Scene Recognition (2015) (9)
Penrose high-dynamic-range imaging (2016) (8)
$\ell_{1}$ -Norm Heteroscedastic Discriminant Analysis Under Mixture of Gaussian Distributions (2019) (8)
On the Complexity Analysis of the Primal Solutions for the Accelerated Randomized Dual Coordinate Ascent (2018) (8)
Optimization Induced Equilibrium Networks: An Explicit Optimization Perspective for Understanding Equilibrium Models (2022) (8)
A Submodule Clustering Method for Multi-way Data by Sparse and Low-Rank Representation (2016) (8)
Tensor LRR based subspace clustering (2014) (8)
A new discriminant subspace analysis approach for multi-class problems (2012) (8)
Training Neural Networks by Lifted Proximal Operator Machines (2020) (8)
Fast Multidimensional Ellipsoid-Specific Fitting by Alternating Direction Method of Multipliers (2016) (8)
DATA: Differentiable ArchiTecture Approximation With Distribution Guided Sampling (2020) (8)
The frequency structure matrix: A representation of color filter arrays (2011) (7)
ROUTE: Robust Outlier Estimation for Low Rank Matrix Recovery (2017) (7)
Optimal Nonergodic $O(1/K)$ Convergence Rate: When Linearized ADM Meets Nesterov's Extrapolation (2016) (7)
Reconstruction regularized low-rank subspace learning for cross-modal retrieval (2021) (7)
PDO-eS2CNNs: Partial Differential Operator Based Equivariant Spherical CNNs (2021) (7)
Image tag completion and refinement by subspace clustering and matrix completion (2015) (7)
A Rank-One Update Algorithm for Fast Solving Kernel Foley–Sammon Optimal Discriminant Vectors (2010) (7)
Structured Sparsity Optimization With Non-Convex Surrogates of $\ell _{2,0}$ℓ2,0-Norm: A Unified Algorithmic Framework (2022) (7)
Introduction to the Issue on Robust Subspace Learning and Tracking: Theory, Algorithms, and Applications (2018) (7)
Restarted Nonconvex Accelerated Gradient Descent: No More Polylogarithmic Factor in the O(ε-7/4) Complexity (2022) (7)
Tensor Q-Rank: A New Data Dependent Tensor Rank (2019) (7)
Super-Resolution in the Detector Layout Domain (2007) (7)
Globally Variance-Constrained Sparse Representation and Its Application in Image Set Coding (2016) (6)
G2CN: Graph Gaussian Convolution Networks with Concentrated Graph Filters (2022) (6)
Adan: Adaptive Nesterov Momentum Algorithm for Faster Optimizing Deep Models (2022) (6)
Optimization-Induced Graph Implicit Nonlinear Diffusion (2022) (6)
A new retraction for accelerating the Riemannian three-factor low-rank matrix completion algorithm (2015) (6)
Optimization Induced Equilibrium Networks (2021) (6)
Binary Multidimensional Scaling for Hashing (2018) (6)
The Augmented Homogeneous Coordinates Matrix-Based Projective Mismatch Removal for Partial-Duplicate Image Search (2019) (6)
Optimal Polynomial Filters (2005) (6)
Optimizing Multi-Class Spatio-Spectral Filters via Bayes Error Estimation for EEG Classification (2009) (5)
Boosted Histogram Transform for Regression (2020) (5)
Restarted Nonconvex Accelerated Gradient Descent: No More Polylogarithmic Factor in the $O(\epsilon^{-7/4})$ Complexity (2022) (5)
Tree Structure Based Analyses on Compressive Sensing for Binary Sparse Sources (2010) (5)
Online Training Through Time for Spiking Neural Networks (2022) (5)
Lorentzian Discriminant Projection and Its Applications (2009) (5)
Prefiltering Two-Dimensional Polygons without Clipping (2005) (5)
A Unified Contrastive Energy-based Model for Understanding the Generative Ability of Adversarial Training (2022) (5)
Solvent Engineering of Highly Conductive and Porous Fullerene Ammonium Iodide for Immobilizing Pd Nanoparticles with Enhanced Electrocatalytic Activity Toward Ethanol Oxidation (2019) (5)
Neural Collapse Inspired Feature-Classifier Alignment for Few-Shot Class Incremental Learning (2023) (5)
Learned Extragradient ISTA with Interpretable Residual Structures for Sparse Coding (2021) (5)
L1-norm global geometric consistency for partial-duplicate image retrieval (2014) (4)
Low Rank Global Geometric Consistency for Partial-Duplicate Image Search (2014) (4)
Factorization for projective and metric reconstruction via truncated nuclear norm (2017) (4)
Correction and rectification of light fields (2003) (4)
Under-bagging Nearest Neighbors for Imbalanced Classification (2021) (4)
Optimization inspired Multi-Branch Equilibrium Models (2022) (4)
Accelerated Algorithms for Constrained Convex Optimization (2020) (4)
One-Shot Approximate Local Shading (2008) (4)
Inducing Neural Collapse in Imbalanced Learning: Do We Really Need a Learnable Classifier at the End of Deep Neural Network? (2022) (4)
Long-Tail Hashing (2021) (4)
Globally Variance-Constrained Sparse Representation for Rate-Distortion Optimized Image Representation (2017) (3)
Automatic Design of High-Sensitivity Color Filter Arrays with Panchromatic Pixels. (2016) (3)
Bases sorting: Generalizing the concept of frequency for over-complete dictionaries (2013) (3)
CerDEQ: Certifiable Deep Equilibrium Model (2022) (3)
First Order Approximation for Texture Filtering (2006) (3)
Fast Compressive Phase Retrieval under Bounded Noise (2017) (3)
GBHT: Gradient Boosting Histogram Transform for Density Estimation (2021) (3)
Chapter 4 – Optimization Algorithms (2017) (3)
Histogram Transform Ensembles for Large-scale Regression (2019) (2)
Exactly Recovering Low-Rank Matrix in Linear Time via $l_1$ Filter (2011) (2)
Rethinking Knowledge Graph Evaluation Under the Open-World Assumption (2022) (2)
Two-Dimensional Weisfeiler-Lehman Graph Neural Networks for Link Prediction (2022) (2)
Channel-Weighted Squeeze-and-Excitation Networks For Epileptic Seizure Detection (2021) (2)
Graph Construction with Label Information for Semi-Supervised Learning (2016) (2)
Adaptive Sharing for Image Classification (2015) (2)
Globally Variance-Constrained Sparse Representation for Image Set Compression (2016) (2)
PDO-s3DCNNs: Partial Differential Operator Based Steerable 3D CNNs (2022) (2)
Patch-level Neighborhood Interpolation: A General and Effective Graph-based Regularization Strategy (2019) (2)
Global Convergence of Over-parameterized Deep Equilibrium Models (2022) (2)
Alternating Direction Method of Multipliers for Machine Learning (2022) (2)
A fast alternating time-splitting approach for learning partial differential equations (2016) (2)
Invertible Rescaling Network and Its Extensions (2022) (2)
Pre-filtering 2 D Polygons without Clipping (2004) (2)
Accelerated Stochastic Algorithms (2020) (2)
Synthetic Depth Transfer for Monocular 3D Object Pose Estimation in the Wild (2020) (1)
Demystifying Adversarial Training via A Unified Probabilistic Framework (2021) (1)
Demosaicking based on channel-correlation adaptive dictionary learning (2018) (1)
On the Lower Bound of Minimizing Polyak-{\L}ojasiewicz functions (2022) (1)
Chapter 2 – Linear Models (2017) (1)
Leveraged Weighted Loss For Partial Label Learning (Supplementary Material) (2021) (1)
Provable accelerated gradient method for nonconvex low rank optimization (2019) (1)
Towards Theoretically Inspired Neural Initialization Optimization (2022) (1)
Recurrent learning with clique structures for prostate sparse-view CT artifacts reduction (2021) (1)
A Hybrid Stochastic-Deterministic Minibatch Proximal Gradient Method for Efficient Optimization and Generalization (2021) (1)
Maximum-and-Concatenation Networks (2020) (1)
Linearized alternating direction method with parallel splitting and adaptive penalty for separable convex programs in machine learning (2014) (1)
Rule-based cleanup of on-line English ink notes (2006) (1)
Learning Optimization-inspired Image Propagation with Control Mechanisms and Architecture Augmentations for Low-level Vision (2020) (1)
SPIDE: A Purely Spike-based Method for Training Feedback Spiking Neural Networks (2023) (1)
Reparameterized Sampling for Generative Adversarial Networks (2021) (1)
Pattern Recognition and Computer Vision: Second Chinese Conference, PRCV 2019, Xi’an, China, November 8–11, 2019, Proceedings, Part II (2019) (1)
A new nonlocal low-rank regularization method with applications to magnetic resonance image denoising (2022) (1)
LION: Implicit Vision Prompt Tuning (2023) (1)
PanopticPartFormer++: A Unified and Decoupled View for Panoptic Part Segmentation (2023) (1)
Linearized Alternating Direction (2012) (1)
Recurrent Neural Networks (2015) (1)
Uncertainty Principles of Encoding GANs (2021) (1)
Fast Algorithms for Recovering a Corrupted (2009) (1)
Gradient Boosted Binary Histogram Ensemble for Large-scale Regression (2021) (1)
Construction of Incoherent Dictionaries via Direct Babel Function Minimization (2018) (1)
Optimization Induced Deep Equilibrium Networks (2022) (1)
TensorlinearLaplaciandiscrimination(TLLD)forfeatureextraction (2009) (0)
Channel-Correlation Adaptive Dictionary Learning based Demosaicking (2018) (0)
Convolutional Transformer Networks for Epileptic Seizure Detection (2022) (0)
Classify and Generate Reciprocally: Simultaneous Positive-Unlabelled Learning and Conditional Generation with Extra Data (2020) (0)
Antialiasing of high quality (2004) (0)
Equilibrium Image Denoising With Implicit Differentiation (2023) (0)
Pattern Recognition and Computer Vision: Second Chinese Conference, PRCV 2019, Xi’an, China, November 8–11, 2019, Proceedings, Part I (2019) (0)
Accelerated Algorithms for Nonconvex Optimization (2020) (0)
SymNMF-Net for The Symmetric NMF Problem (2022) (0)
Material of Faster and Non-ergodic O ( 1 / K ) Stochastic Alternating Direction Method of Multipliers (2017) (0)
Pattern Recognition and Computer Vision: Second Chinese Conference, PRCV 2019, Xi’an, China, November 8–11, 2019, Proceedings, Part III (2019) (0)
Fast,automaticandfine-grainedtamperedJPEGimagedetection viaDCTcoefficientanalysis (2009) (0)
Chapter 3 – Nonlinear Models (2017) (0)
Accelerated Alternating Direction Method of Multipliers: An Optimal O(1 / K) Nonergodic Analysis (2018) (0)
Appendix A – Proofs (2017) (0)
Tensor Recovery With Weighted Tensor Average Rank. (2022) (0)
Supplementary Material: Deep Comprehensive Correlation Mining for Image Clustering (2019) (0)
Provable Particle-based Primal-Dual Algorithm for Mixed Nash Equilibrium (2023) (0)
Kill a Bird with Two Stones: Closing the Convergence Gaps in Non-Strongly Convex Optimization by Directly Accelerated SVRG with Double Compensation and Snapshots (2022) (0)
Noise-Aware Subspace Clustering (2016) (0)
Tensor principal component analysis (2022) (0)
Uncertainty Principles of Encoding GANs Supplementary Material (2021) (0)
Accelerated Parallel Algorithms (2020) (0)
sparse graph LRR release (2015) (0)
AdaptiveSharing for Image Classification (2015) (0)
Correction and rectification of light field (2002) (0)
Towards Memory- and Time-Efficient Backpropagation for Training Spiking Neural Networks (2023) (0)
Problem : Regularized Optimization for Inducing Block-diagonal Matrices (2015) (0)
Neural Ordinary Differential Equations with Envolutionary Weights (2019) (0)
C HAOS IS A L ADDER : A N EW T HEORETICAL U N DERSTANDING OF C ONTRASTIVE L EARNING VIA A UG MENTATION O VERLAP (2022) (0)
Chapter 5 – Representative Applications (2017) (0)
Chapter 6 – Conclusions (2017) (0)
Quantized Neural Networks via {-1, +1} Encoding Decomposition and Acceleration (2021) (0)
Conclusions (2020) (0)
A Message Passing Perspective on Learning Dynamics of Contrastive Learning (2023) (0)
Accelerated Algorithms for Unconstrained Convex Optimization (2020) (0)
EnTranNAS: Towards Closing the Gap between the Architectures in Search and Evaluation (2020) (0)
Fast and Differentiable Matrix Inverse and Its Extension to SVD (2020) (0)
Table Detection in On-line Ink Notes (2005) (0)
Supplementary Materials : Bilinear Factor Matrix Norm Minimization for Robust PCA : Algorithms and Applications (2017) (0)
Appendix B – Mathematical Preliminaries (2017) (0)
The Shape Interaction Matrix-Based Affine Invariant Mismatch Removal for Partial-Duplicate Image Search. (2017) (0)
Determining step sizes in geometric optimization algorithms (2015) (0)
A U NIFIED C ONTRASTIVE E NERGY - BASED M ODEL FOR U NDERSTANDING THE G ENERATIVE A BILITY OF A DVERSARIAL T RAINING (2022) (0)
Transform invariant text extraction (2013) (0)
Accelerated Gradient Method for A Class of Nonconvex Low Rank Problem: Essentially Matching the Optimal Convex Convergence Rate (2017) (0)
Pareto Adversarial Robustness: Balancing Spatial Robustness and Sensitivity-based Robustness (2021) (0)
Introduction (2020) (0)
Subspace Clustering Based Tag Sharing for Inductive Tag Matrix Refinement with Complex Errors (2016) (0)
Refined Exponential Filter with Applications to Image Restoration and Interpolation (2009) (0)
Efficient and Scalable Implicit Graph Neural Networks with Virtual Equilibrium (2022) (0)
Supplementary Material of Generalized Singular Value Thresholding (2014) (0)

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