Shiweiliuiiiiiii / Selfish-RNN
[ICML 2021] "Selfish Sparse RNN Training" by Shiwei Liu, Decebal Constantin Mocanu, Yulong Pei, Mykola Pechenizkiy
☆10Updated 3 years ago
Related projects ⓘ
Alternatives and complementary repositories for Selfish-RNN
- [NeurIPS‘2021] "MEST: Accurate and Fast Memory-Economic Sparse Training Framework on the Edge", Geng Yuan, Xiaolong Ma, Yanzhi Wang et al…☆18Updated 2 years ago
- This is the pytorch implementation for the paper: Generalizable Mixed-Precision Quantization via Attribution Rank Preservation, which is…☆24Updated 3 years ago
- [ICML 2021] "Do We Actually Need Dense Over-Parameterization? In-Time Over-Parameterization in Sparse Training" by Shiwei Liu, Lu Yin, De…☆46Updated last year
- ☆11Updated 2 years ago
- [ICLR 2021] "Long Live the Lottery: The Existence of Winning Tickets in Lifelong Learning" by Tianlong Chen*, Zhenyu Zhang*, Sijia Liu, S…☆23Updated 2 years ago
- BESA is a differentiable weight pruning technique for large language models.☆14Updated 8 months ago
- Revisiting Parameter Sharing for Automatic Neural Channel Number Search, NeurIPS 2020☆20Updated 4 years ago
- Code for ICML 2021 submission☆35Updated 3 years ago
- Breaking the Curse of Space Explosion: Towards Efficient NAS with Curriculum Search☆17Updated 3 months ago
- Official code of "NAS acceleration via proxy data", IJCAI21☆10Updated 2 years ago
- [ICLR 2022] "Unified Vision Transformer Compression" by Shixing Yu*, Tianlong Chen*, Jiayi Shen, Huan Yuan, Jianchao Tan, Sen Yang, Ji Li…☆48Updated 11 months ago
- [TMLR] Official PyTorch implementation of paper "Efficient Quantization-aware Training with Adaptive Coreset Selection"☆29Updated 3 months ago
- [ICLR 2022] The Unreasonable Effectiveness of Random Pruning: Return of the Most Naive Baseline for Sparse Training by Shiwei Liu, Tianlo…☆73Updated last year
- [ICML 2021 Oral] "CATE: Computation-aware Neural Architecture Encoding with Transformers" by Shen Yan, Kaiqiang Song, Fei Liu, Mi Zhang☆19Updated 3 years ago
- [Preprint] Why is the State of Neural Network Pruning so Confusing? On the Fairness, Comparison Setup, and Trainability in Network Prunin…☆40Updated last year
- ☆10Updated 3 years ago
- Pytorch implementation of our paper (TNNLS) -- Pruning Networks with Cross-Layer Ranking & k-Reciprocal Nearest Filters☆12Updated 2 years ago
- [ICCV-2023] EMQ: Evolving Training-free Proxies for Automated Mixed Precision Quantization☆27Updated 11 months ago
- Official codebase for our paper "Joslim: Joint Widths and Weights Optimization for Slimmable Neural Networks"☆12Updated 3 years ago
- ☆24Updated 2 years ago
- ☆23Updated 2 years ago
- Official PyTorch Implementation of "Learning Architectures for Binary Networks" (ECCV2020)☆26Updated 4 years ago
- To appear in the 11th International Conference on Learning Representations (ICLR 2023).☆16Updated last year
- Data-Free Neural Architecture Search via Recursive Label Calibration. ECCV 2022.☆32Updated 2 years ago
- The code for Joint Neural Architecture Search and Quantization☆13Updated 5 years ago
- ☆11Updated 5 months ago
- Pytorch implementation of our paper accepted by IEEE TNNLS, 2021 -- Network Pruning using Adaptive Exemplar Filters☆22Updated 3 years ago
- [NeurIPS 2019] E2-Train: Training State-of-the-art CNNs with Over 80% Less Energy☆21Updated 5 years ago
- [Neurips 2021] Sparse Training via Boosting Pruning Plasticity with Neuroregeneration☆29Updated last year
- ☆10Updated last year