IST-DASLab / spdyLinks
Code for ICML 2022 paper "SPDY: Accurate Pruning with Speedup Guarantees"
☆19Updated 2 years ago
Alternatives and similar repositories for spdy
Users that are interested in spdy are comparing it to the libraries listed below
Sorting:
- [ICCV-2023] EMQ: Evolving Training-free Proxies for Automated Mixed Precision Quantization☆26Updated last year
- You Only Search Once: On Lightweight Differentiable Architecture Search for Resource-Constrained Embedded Platforms☆11Updated 2 years ago
- ☆25Updated 3 years ago
- Qimera: Data-free Quantization with Synthetic Boundary Supporting Samples [NeurIPS 2021]☆33Updated 3 years ago
- ☆43Updated last year
- Post-training sparsity-aware quantization☆34Updated 2 years ago
- Code for ICML 2021 submission☆34Updated 4 years ago
- [TMLR] Official PyTorch implementation of paper "Efficient Quantization-aware Training with Adaptive Coreset Selection"☆33Updated 10 months ago
- Official implementation of the EMNLP23 paper: Outlier Suppression+: Accurate quantization of large language models by equivalent and opti…☆46Updated last year
- [ICLR'23] Trainability Preserving Neural Pruning (PyTorch)☆33Updated 2 years ago
- ☆25Updated 3 years ago
- [ICLR 2022] "Learning Pruning-Friendly Networks via Frank-Wolfe: One-Shot, Any-Sparsity, and No Retraining" by Lu Miao*, Xiaolong Luo*, T…☆30Updated 3 years ago
- Generic Neural Architecture Search via Regression (NeurIPS'21 Spotlight)☆36Updated 2 years ago
- [ICLR 2021] HW-NAS-Bench: Hardware-Aware Neural Architecture Search Benchmark☆110Updated 2 years ago
- This project is the official implementation of our accepted IEEE TPAMI paper Diverse Sample Generation: Pushing the Limit of Data-free Qu…☆14Updated 2 years ago
- [NeurIPS 2021] “Stronger NAS with Weaker Predictors“, Junru Wu, Xiyang Dai, Dongdong Chen, Yinpeng Chen, Mengchen Liu, Ye Yu, Zhangyang W…☆27Updated 2 years ago
- [NeurIPS‘2021] "MEST: Accurate and Fast Memory-Economic Sparse Training Framework on the Edge", Geng Yuan, Xiaolong Ma, Yanzhi Wang et al…☆18Updated 3 years ago
- A collection of research papers on efficient training of DNNs☆70Updated 2 years ago
- [ICML 2022] "Coarsening the Granularity: Towards Structurally Sparse Lottery Tickets" by Tianlong Chen, Xuxi Chen, Xiaolong Ma, Yanzhi Wa…☆33Updated 2 years ago
- [Neurips 2021] Sparse Training via Boosting Pruning Plasticity with Neuroregeneration☆31Updated 2 years ago
- [Preprint] Why is the State of Neural Network Pruning so Confusing? On the Fairness, Comparison Setup, and Trainability in Network Prunin…☆40Updated 2 years ago
- Pytorch implementation of our paper accepted by ICML 2023 -- "Bi-directional Masks for Efficient N:M Sparse Training"☆12Updated 2 years ago
- [ICML 2021] "Do We Actually Need Dense Over-Parameterization? In-Time Over-Parameterization in Sparse Training" by Shiwei Liu, Lu Yin, De…☆45Updated last year
- NAS Benchmark in "Prioritized Architecture Sampling with Monto-Carlo Tree Search", CVPR2021☆37Updated 3 years ago
- Towards Compact CNNs via Collaborative Compression☆11Updated 3 years ago
- PyTorch implementation of Towards Efficient Training for Neural Network Quantization☆15Updated 5 years ago
- ☆12Updated last year
- BitSplit Post-trining Quantization☆50Updated 3 years ago
- Position-based Scaled Gradient for Model Quantization and Pruning Code (NeurIPS 2020)☆26Updated 4 years ago
- [ICLR 2021 Spotlight] "CPT: Efficient Deep Neural Network Training via Cyclic Precision" by Yonggan Fu, Han Guo, Meng Li, Xin Yang, Yinin…☆31Updated last year