network pruning

Can We Find Strong Lottery Tickets in Generative Models? AAAI 2023 Compact and Optimal Deep Learning With Recurrent Parameter Generators WACV 2023 Compressing and Debiasing Vision-Language Pre-Trained Models for Visual Question Answering EMNLP 2023 Efficient Latency-Aware CNN Depth Compression via Two-Stage Dynamic Programming ICML 2023 ESL-SNNs: An Evolutionary Structure Learning Strategy for Spiking Neural Networks AAAI 2023 Exploring Temporal Information Dynamics in Spiking Neural Networks AAAI 2023 Fair Scratch Tickets: Finding Fair Sparse Networks Without Weight Training CVPR 2023 Graph Structure Learning via Lottery Hypothesis at Scale ACML 2023 How a Student becomes a Teacher: learning and forgetting through Spectral methods NeurIPS 2023 Iterative Soft Shrinkage Learning for Efficient Image Super-Resolution ICCV 2023 Learning Adversarially Robust Sparse Networks via Weight Reparameterization AAAI 2023 Lottery Tickets in Evolutionary Optimization: On Sparse Backpropagation-Free Trainability ICML 2023 MECTA: Memory-Economic Continual Test-Time Model Adaptation ICLR 2023 On the Neural Tangent Kernel Analysis of Randomly Pruned Neural Networks AISTATS 2023 Pruning Deep Neural Networks from a Sparsity Perspective ICLR 2023 Pruning-Guided Curriculum Learning for Semi-Supervised Semantic Segmentation WACV 2023 Quantifying lottery tickets under label noise: accuracy, calibration, and complexity UAI 2023 Re-GAN: Data-Efficient GANs Training via Architectural Reconfiguration CVPR 2023 Resilient Binary Neural Network AAAI 2023 Rethinking Graph Lottery Tickets: Graph Sparsity Matters ICLR 2023 REVISITING PRUNING AT INITIALIZATION THROUGH THE LENS OF RAMANUJAN GRAPH ICLR 2023 Searching Lottery Tickets in Graph Neural Networks: A Dual Perspective ICLR 2023 Strong Lottery Ticket Hypothesis with ε–perturbation AISTATS 2023 Structural Alignment for Network Pruning through Partial Regularization ICCV 2023 The Emergence of Essential Sparsity in Large Pre-trained Models: The Weights that Matter NeurIPS 2023