Zhouchen Lin

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 $O(ε^-7/4)$ 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