← Authors

Zhouchen Lin

120 papers · 2007–2026 · 12 conferences · across top CS/AI conferences

Achievements

🧭 Keyword Pioneer 🐝 Cross-Pollinator (11) πŸƒ Academic Marathon (18) 🌍 Conference Polyglot (12) 🐣 Hot Topic Early Bird 🌈 Renaissance Researcher (6) πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (27) 🌟 Keyword Trendsetter Combo (5) 🏠 Conference Loyalist (23) πŸ† Keyword Champion 🀝 Dynamic Duo (22) πŸ† Grand Slam πŸ‘‘ Triple Crown πŸ”¬ Deep Specialist (28) 🧬 Topic Evolution πŸ“ˆ Trend Setter πŸ”₯ Unstoppable (13) πŸš€ Conference Pioneer πŸ’Ž Century Club (118) ❓ The Questioner (2) πŸ—ƒοΈ Keyword Collector (96) ⚑ Prolific Year (17)

Conferences

NIPS (23) ICML (21) CVPR (16) ICLR (16) AAAI (11) JMLR (10) ICCV (7) IJCAI (5) ACML (4) COLT (3) ECCV (3) AISTATS (1)

Top co-authors

Yisen Wang (22) Yibo Yang (13) Cong Fang (11) Yifei Wang (9) Huan Li (9) Jianlong Wu (9) Xingyu Xie (8) Xia Li (8) Mingqing Xiao (7) Jiansheng Yang (7)

Research topics

Core AI (1)

Keywords

convolutional neural network (8) convex optimization (7) gradient descent (7) neural network (7) affinity matrix (6) convergence rate (6) subspace clustering (6) stochastic optimization (5) nonconvex optimization (5) neural network optimization (5) deep equilibrium model (4) stochastic gradient descent (4) semantic segmentation (4) spiking neural network (4) low-rank representation (4) neuromorphic computing (4) alternating direction method (4) graph laplacian (3) spectral clustering (3) neural network architecture (3)

Papers

Uplift Modeling with Delayed Feedback: Identifiability and Algorithms AAAI 2026
FedAdamW: A Communication-Efficient Optimizer with Convergence and Generalization Guarantees for Federated Large Models AAAI 2026
Pyramidal Flow Matching for Efficient Video Generative Modeling ICLR 2025
Affine Steerable Equivariant Layer for Canonicalization of Neural Networks ICLR 2025
High-Rank Irreducible Cartesian Tensor Decomposition and Bases of Equivariant Spaces JMLR 2025
Active Treatment Effect Estimation via Limited Samples ICML 2025
Incorporating Arbitrary Matrix Group Equivariance into KANs ICML 2025
Explicit Discovery of Nonlinear Symmetries from Dynamic Data ICML 2025
Low-Dimension-to-High-Dimension Generalization and Its Implications for Length Generalization ICML 2025
On the O(sqrt(d)/T^(1/4)) Convergence Rate of RMSProp and Its Momentum Extension Measured by l_1 Norm JMLR 2025
Empowering LLMs with Logical Reasoning: A Comprehensive Survey IJCAI 2025
Unbiased Recommender Learning from Implicit Feedback via Weakly Supervised Learning ICML 2025
Number Cookbook: Number Understanding of Language Models and How to Improve It ICLR 2025
TC-MoE: Augmenting Mixture of Experts with Ternary Expert Choice ICLR 2025
SEPARATE: A Simple Low-rank Projection for Gradient Compression in Modern Large-scale Model Training Process ICLR 2025
Hebbian Learning based Orthogonal Projection for Continual Learning of Spiking Neural Networks ICLR 2024
Temporal Spiking Neural Networks with Synaptic Delay for Graph Reasoning ICML 2024
Affine Equivariant Networks Based on Differential Invariants CVPR 2024
Win: Weight-Decay-Integrated Nesterov Acceleration for Faster Network Training JMLR 2024
LION: Implicit Vision Prompt Tuning AAAI 2024
PAPAL: A Provable PArticle-based Primal-Dual ALgorithm for Mixed Nash Equilibrium JMLR 2024
Accelerated Gradient Tracking over Time-varying Graphs for Decentralized Optimization JMLR 2024
Separation and Bias of Deep Equilibrium Models on Expressivity and Learning Dynamics NIPS 2024
Relational Learning in Pre-Trained Models: A Theory from Hypergraph Recovery Perspective ICML 2024
KDLGT: A Linear Graph Transformer Framework via Kernel Decomposition Approach IJCAI 2023
Neural ePDOs: Spatially Adaptive Equivariant Partial Differential Operator Based Networks ICLR 2023
Neural Collapse Inspired Feature-Classifier Alignment for Few-Shot Class-Incremental Learning ICLR 2023
Unbiased Stochastic Proximal Solver for Graph Neural Networks with Equilibrium States ICLR 2023
A Message Passing Perspective on Learning Dynamics of Contrastive Learning ICLR 2023
Towards Memory- and Time-Efficient Backpropagation for Training Spiking Neural Networks ICCV 2023
Task-Robust Pre-Training for Worst-Case Downstream Adaptation NIPS 2023
Balance, Imbalance, and Rebalance: Understanding Robust Overfitting from a Minimax Game Perspective NIPS 2023
GEQ: Gaussian Kernel Inspired Equilibrium Models NIPS 2023
A Single-Loop Accelerated Extra-Gradient Difference Algorithm with Improved Complexity Bounds for Constrained Minimax Optimization NIPS 2023
Restarted Nonconvex Accelerated Gradient Descent: No More Polylogarithmic Factor in the in the O(epsilon^(-7/4)) Complexity JMLR 2023
Patch-level Neighborhood Interpolation: A General and Effective Graph-based Regularization Strategy ACML 2023
Global Convergence of Over-parameterized Deep Equilibrium Models AISTATS 2023
On the Lower Bound of Minimizing Polyak-Łojasiewicz functions COLT 2023
Zeroth-order Optimization with Weak Dimension Dependency COLT 2023
Training High-Performance Low-Latency Spiking Neural Networks by Differentiation on Spike Representation CVPR 2022
Variance Reduced EXTRA and DIGing and Their Optimal Acceleration for Strongly Convex Decentralized Optimization JMLR 2022
PDO-s3DCNNs: Partial Differential Operator Based Steerable 3D CNNs ICML 2022
Kill a Bird with Two Stones: Closing the Convergence Gaps in Non-Strongly Convex Optimization by Directly Accelerated SVRG with Double Compensation and Snapshots ICML 2022
CerDEQ: Certifiable Deep Equilibrium Model ICML 2022
Restarted Nonconvex Accelerated Gradient Descent: No More Polylogarithmic Factor in the $O(Ξ΅^-7/4)$ Complexity ICML 2022
G$^2$CN: Graph Gaussian Convolution Networks with Concentrated Graph Filters ICML 2022
Optimization-Induced Graph Implicit Nonlinear Diffusion ICML 2022
Inducing Neural Collapse in Imbalanced Learning: Do We Really Need a Learnable Classifier at the End of Deep Neural Network? NIPS 2022
Online Training Through Time for Spiking Neural Networks NIPS 2022
Towards Theoretically Inspired Neural Initialization Optimization NIPS 2022
Rethinking Knowledge Graph Evaluation Under the Open-World Assumption NIPS 2022
Chaos is a Ladder: A New Theoretical Understanding of Contrastive Learning via Augmentation Overlap ICLR 2022
A Unified Contrastive Energy-based Model for Understanding the Generative Ability of Adversarial Training ICLR 2022
Under-bagging Nearest Neighbors for Imbalanced Classification JMLR 2022
Optimization inspired Multi-Branch Equilibrium Models ICLR 2022
PDO-eS2CNNs: Partial Differential Operator Based Equivariant Spherical CNNs AAAI 2021
Efficient Equivariant Network NIPS 2021
Dissecting the Diffusion Process in Linear Graph Convolutional Networks NIPS 2021
Residual Relaxation for Multi-view Representation Learning NIPS 2021
Training Feedback Spiking Neural Networks by Implicit Differentiation on the Equilibrium State NIPS 2021
On Training Implicit Models NIPS 2021
Gauge Equivariant Transformer NIPS 2021
Learned Extragradient ISTA with Interpretable Residual Structures for Sparse Coding AAAI 2021
Towards Improving the Consistency, Efficiency, and Flexibility of Differentiable Neural Architecture Search CVPR 2021
PointFlow: Flowing Semantics Through Points for Aerial Image Segmentation CVPR 2021
Graph Contrastive Clustering ICCV 2021
Is Attention Better Than Matrix Decomposition? ICLR 2021
AdaGCN: Adaboosting Graph Convolutional Networks into Deep Models ICLR 2021
GBHT: Gradient Boosting Histogram Transform for Density Estimation ICML 2021
Uncertainty Principles of Encoding GANs ICML 2021
Leveraged Weighted Loss for Partial Label Learning ICML 2021
Histogram Transform Ensembles for Large-scale Regression JMLR 2021
Maximum-and-Concatenation Networks ICML 2020
SOGNet: Scene Overlap Graph Network for Panoptic Segmentation AAAI 2020
Improving Semantic Segmentation via Decoupled Body and Edge Supervision ECCV 2020
Invertible Image Rescaling ECCV 2020
Multi-Stage Self-Supervised Learning for Graph Convolutional Networks on Graphs with Few Labeled Nodes AAAI 2020
Spatial Pyramid Based Graph Reasoning for Semantic Segmentation CVPR 2020
Unified Graph and Low-Rank Tensor Learning for Multi-View Clustering AAAI 2020
On the Complexity Analysis of the Primal Solutions for the Accelerated Randomized Dual Coordinate Ascent JMLR 2020
Dynamical System Inspired Adaptive Time Stepping Controller for Residual Network Families AAAI 2020
Synthetic Depth Transfer for Monocular 3D Object Pose Estimation in the Wild AAAI 2020
ISTA-NAS: Efficient and Consistent Neural Architecture Search by Sparse Coding NIPS 2020
Boosted Histogram Transform for Regression ICML 2020
Implicit Euler Skip Connections: Enhancing Adversarial Robustness via Numerical Stability ICML 2020
PDO-eConvs: Partial Differential Operator Based Equivariant Convolutions ICML 2020
Self-Supervised Convolutional Subspace Clustering Network CVPR 2019
Differentiable Linearized ADMM ICML 2019
Sharp Analysis for Nonconvex SGD Escaping from Saddle Points COLT 2019
Lifted Proximal Operator Machines AAAI 2019
Expectation-Maximization Attention Networks for Semantic Segmentation ICCV 2019
Deep Comprehensive Correlation Mining for Image Clustering ICCV 2019
Joint Sub-bands Learning with Clique Structures for Wavelet Domain Super-Resolution NIPS 2018
Exact Low Tubal Rank Tensor Recovery from Gaussian Measurements IJCAI 2018
Alternating Multi-bit Quantization for Recurrent Neural Networks ICLR 2018
Recurrent Squeeze-and-Excitation Context Aggregation Net for Single Image Deraining ECCV 2018
Convolutional Neural Networks With Alternately Updated Clique CVPR 2018
SPIDER: Near-Optimal Non-Convex Optimization via Stochastic Path-Integrated Differential Estimator NIPS 2018
Optimization Algorithm Inspired Deep Neural Network Structure Design ACML 2018
Construction of Incoherent Dictionaries via Direct Babel Function Minimization ACML 2018
Faster and Non-ergodic O(1/K) Stochastic Alternating Direction Method of Multipliers NIPS 2017
ROUTE: Robust Outlier Estimation for Low Rank Matrix Recovery IJCAI 2017
Tensor Robust Principal Component Analysis: Exact Recovery of Corrupted Low-Rank Tensors via Convex Optimization CVPR 2016
Robust Kernel Estimation With Outliers Handling for Image Deblurring CVPR 2016
Subspace Clustering by Mixture of Gaussian Regression CVPR 2015
Adaptive Sharing for Image Classification IJCAI 2015
Learning Semi-Supervised Representation Towards a Unified Optimization Framework for Semi-Supervised Learning ICCV 2015
Accelerated Proximal Gradient Methods for Nonconvex Programming NIPS 2015
A New Retraction for Accelerating the Riemannian Three-Factor Low-Rank Matrix Completion Algorithm CVPR 2015
Robust Estimation of 3D Human Poses from a Single Image CVPR 2014
Robust Subspace Segmentation with Block-diagonal Prior CVPR 2014
Smooth Representation Clustering CVPR 2014
Adaptive Partial Differential Equation Learning for Visual Saliency Detection CVPR 2014
Generalized Nonconvex Nonsmooth Low-Rank Minimization CVPR 2014
Linearized Alternating Direction Method with Parallel Splitting and Adaptive Penalty for Separable Convex Programs in Machine Learning ACML 2013
Correntropy Induced L2 Graph for Robust Subspace Clustering ICCV 2013
Correlation Adaptive Subspace Segmentation by Trace Lasso ICCV 2013
Linearized Alternating Direction Method with Adaptive Penalty for Low-Rank Representation NIPS 2011
Optimizing Multi-Class Spatio-Spectral Filters via Bayes Error Estimation for EEG Classification NIPS 2009
Classification via Minimum Incremental Coding Length (MICL) NIPS 2007