sparse-training

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google-research / rigl

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End-to-end training of sparse deep neural networks with little-to-no performance loss.

machine-learning computer-vision neural-networks sparse-training

Updated Jan 26, 2023
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dcmocanu / sparse-evolutionary-artificial-neural-networks

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Always sparse. Never dense. But never say never. A Sparse Training repository for the Adaptive Sparse Connectivity concept and its algorithmic instantiation, i.e. Sparse Evolutionary Training, to boost Deep Learning scalability on various aspects (e.g. memory and computational time efficiency, representation and generalization power).

deep-neural-networks sparsity deep-learning scalability randomization neuroevolution deep-learning-algorithms classification evolutionary-algorithms artificial-neural-networks restricted-boltzmann-machine complex-networks deep-learning-papers multi-layer-perceptron generative-models sparse-neural-networks scalable-deep-learning sparse-training sparse-evolutionary-training adaptive-sparse-connectivity

Updated Jul 21, 2021
Python

VITA-Group / SViTE

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[NeurIPS'21] "Chasing Sparsity in Vision Transformers: An End-to-End Exploration" by Tianlong Chen, Yu Cheng, Zhe Gan, Lu Yuan, Lei Zhang, Zhangyang Wang

pruning model-compression sparse-training vision-transformers efficient-transformers dynamic-sparsity token-slimming

Updated Dec 1, 2023
Python

Shiweiliuiiiiiii / In-Time-Over-Parameterization

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[ICML 2021] "Do We Actually Need Dense Over-Parameterization? In-Time Over-Parameterization in Sparse Training" by Shiwei Liu, Lu Yin, Decebal Constantin Mocanu, Mykola Pechenizkiy

sparsity deep-learning generalization sparse-training over-parameterization overparameterization in-time-overparameterization dynamic-sparse-training in-time-over-parameterization

Updated Nov 11, 2023
Python

VITA-Group / ToST

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[ICML2022] Training Your Sparse Neural Network Better with Any Mask. Ajay Jaiswal, Haoyu Ma, Tianlong Chen, ying Ding, and Zhangyang Wang

sparsity lottery-tickets sparse-training

Updated Jul 24, 2022
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zahraatashgahi / QuickSelection

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[Machine Learning Journal (ECML-PKDD 2022 journal track)] Quick and Robust Feature Selection: the Strength of Energy-efficient Sparse Training for Autoencoders

sparsity deep-learning feature-selection autoencoder dimensionality-reduction denoising-autoencoders sparse-neural-networks sparse-training

Updated Oct 2, 2023
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GhadaSokar / Dynamic-Sparse-Training-for-Deep-Reinforcement-Learning

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[IJCAI 2022] "Dynamic Sparse Training for Deep Reinforcement Learning" by Ghada Sokar, Elena Mocanu , Decebal Constantin Mocanu, Mykola Pechenizkiy, and Peter Stone.

deep-neural-networks sparsity reinforcement-learning deep-learning deep-reinforcement-learning sparse-neural-networks sparse-training continuous-control-tasks