Zlin’s Extraordinary Research Oasis

Zeal, Excellence, Reliability and Openness

Welcome to the ZERO Lab, the research group lead by Prof. Zhouchen Lin (Zlin), affiliated to School of Artificial Intelligence, Peking University. We research on machine learning and computer vision.


  • Our group at Peking University is recruiting tenure-track faculties and PostDocs (academic or industrial). For the postdoc program in 2020, please refer to the Chinese version or the English version.
  • Our group at Peking University is recruiting Ph.D.s who have strong mathematical abilities (however, this does not imply that you have to come from mathematics department) and great interest in theoretical analysis in order to enjoy with me how to use mathematics to solve real problems elegantly.


Acceleration ADMM Adversarial Robustness Adversarial Transferability Alternating direction method Alternating Direction Method of Multipliers Bayes error Boosting Color Filter Array Compressed Sensing Compressive Phase Retrieval, computer vision Contextual distance Convergence Analysis Convex Optimization Data Compression Deep Learning Demosaicking Denoising Dictionary Learning Dimensionality reduction Discriminant analysis Document analysis Double quantization Expectation Maximization Face recognition Feature detection Feature extraction forgery Geometric Optimization Handwriting recognition Image Annotation Image classification Image Denoising Image Processing Image Reconstruction Image rectification Image restoration Image Retrieval Image segmentation Laplace equations Learning-based PDEs Light field Linear discriminant analysis Lorentzian geometry Low Rank Low Rank Representation Low-level vision Lumigraph Machine Learning Majorization Minimization Manifold learning Manifolds Matrix Completion matrix decomposition Metric learning Mismatch Removal Neural Network Neural networks Nonconvex Optimization Optimal control Optimization Partial Differential Equation plenoptic functions Pose Estimation Principal component analysis Robust PCA Robust Principal Component Analysis sampling Semantic segmentation Semi-supervised learning Singular value decomposition Sparse Coding Sparse matrices Sparse Representation Spectral clustering Subspace clustering Subspace Recovery Super-Resolution Superresolution

Latest Publications

Neural ePDOs: Spatially Adaptive Equivariant Partial Differential Operator Based Networks. ICLR, 2023.

Endowing deep learning models with symmetry priors can lead to a considerable performance improvement. As an interesting bridge between …

Restarted Nonconvex Accelerated Gradient Descent: No More Polylogarithmic Factor in the O(ε−7/4) Complexity. JMLR, 2023.

This paper studies accelerated gradient methods for nonconvex optimization with Lipschitz continuous gradient and Hessian. We propose …

On the Lower Bound of Minimizing Polyak-Łojasiewicz Functions. COLT, 2023.

Polyak-Łojasiewicz (PL) [Polyak, 1963] condition is a weaker condition than the strong convexity but suffices to ensure a global …

Zeroth-order Optimization with Weak Dimension Dependency. COLT, 2023.

Zeroth-order optimization is a fundamental research topic that has been a focus of various learning tasks, such as black-box …

Optimization-induced Implicit Graph Diffusion. ICML, 2022.

Due to the over-smoothing issue, most existing graph neural networks can only capture limited de- pendencies with their inherently …

Alternating Direction Method of Multipliers for Machine Learning. Springer Singapore, 2022.

Machine learning heavily relies on optimization algorithms to solve its learning models. Constrained problems constitute a major type …

Training Much Deeper Spiking Neural Networks with a Small Number of Time-Steps. Neural Networks, 2022.

Spiking Neural Network (SNN) is a promising energy-efficient neural architecture when implemented on neuromorphic hardware. The …

Training High-Performance Low-Latency Spiking Neural Networks by Differentiation on Spike Representation. CVPR, 2022.

Spiking Neural Network (SNN) is a promising energy-efficient AI model when implemented on neuromorphic hardware. However, it is a …


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