Zhouchen Lin

44

Papers

49

Total Citations

Papers (44)

LION: Implicit Vision Prompt Tuning

Hebbian Learning based Orthogonal Projection for Continual Learning of Spiking Neural Networks

Stepsize anything: A unified learning rate schedule for budgeted-iteration training

Relational Learning in Pre-Trained Models: A Theory from Hypergraph Recovery Perspective

Temporal Spiking Neural Networks with Synaptic Delay for Graph Reasoning

Subspace Clustering by Mixture of Gaussian Regression

A New Retraction for Accelerating the Riemannian Three-Factor Low-Rank Matrix Completion Algorithm

Robust Kernel Estimation With Outliers Handling for Image Deblurring

Convolutional Neural Networks With Alternately Updated Clique

Self-Supervised Convolutional Subspace Clustering Network

Spatial Pyramid Based Graph Reasoning for Semantic Segmentation

Towards Improving the Consistency, Efficiency, and Flexibility of Differentiable Neural Architecture Search

PointFlow: Flowing Semantics Through Points for Aerial Image Segmentation

Training High-Performance Low-Latency Spiking Neural Networks by Differentiation on Spike Representation

Learning Semi-Supervised Representation Towards a Unified Optimization Framework for Semi-Supervised Learning

Deep Comprehensive Correlation Mining for Image Clustering

Expectation-Maximization Attention Networks for Semantic Segmentation

Graph Contrastive Clustering

Towards Memory- and Time-Efficient Backpropagation for Training Spiking Neural Networks

Invertible Image Rescaling

Improving Semantic Segmentation via Decoupled Body and Edge Supervision

Accelerated Proximal Gradient Methods for Nonconvex Programming

Faster and Non-ergodic O(1/K) Stochastic Alternating Direction Method of Multipliers

NeurIPS 2017arXiv

Tensor Robust Principal Component Analysis: Exact Recovery of Corrupted Low-Rank Tensors via Convex Optimization

Affine Equivariant Networks Based on Differential Invariants

Explicit Discovery of Nonlinear Symmetries from Dynamic Data

SPIDER: Near-Optimal Non-Convex Optimization via Stochastic Path-Integrated Differential Estimator

Joint Sub-bands Learning with Clique Structures for Wavelet Domain Super-Resolution

ISTA-NAS: Efficient and Consistent Neural Architecture Search by Sparse Coding

Efficient Equivariant Network

Dissecting the Diffusion Process in Linear Graph Convolutional Networks

Residual Relaxation for Multi-view Representation Learning

Training Feedback Spiking Neural Networks by Implicit Differentiation on the Equilibrium State

On Training Implicit Models

Gauge Equivariant Transformer

Rethinking Knowledge Graph Evaluation Under the Open-World Assumption

Towards Theoretically Inspired Neural Initialization Optimization

Online Training Through Time for Spiking Neural Networks

Inducing Neural Collapse in Imbalanced Learning: Do We Really Need a Learnable Classifier at the End of Deep Neural Network?

Task-Robust Pre-Training for Worst-Case Downstream Adaptation

Balance, Imbalance, and Rebalance: Understanding Robust Overfitting from a Minimax Game Perspective

GEQ: Gaussian Kernel Inspired Equilibrium Models

A Single-Loop Accelerated Extra-Gradient Difference Algorithm with Improved Complexity Bounds for Constrained Minimax Optimization

Differentiable Linearized ADMM