model pruning

Provable Benefits of Overparameterization in Model Compression: From Double Descent to Pruning Neural Networks AAAI 2021 Pruning-then-Expanding Model for Domain Adaptation of Neural Machine Translation NAACL 2021 Robust error bounds for quantised and pruned neural networks L4DC 2021 Sparse Flows: Pruning Continuous-depth Models NeurIPS 2021 TacoLPCNet: Fast and Stable TTS by Conditioning LPCNet on Mel Spectrogram Predictions Interspeech 2021 The Lottery Ticket Hypothesis for Object Recognition CVPR 2021 The Lottery Tickets Hypothesis for Supervised and Self-Supervised Pre-Training in Computer Vision Models CVPR 2021 The Low-Resource Double Bind: An Empirical Study of Pruning for Low-Resource Machine Translation EMNLP 2021 TransTailor: Pruning the Pre-trained Model for Improved Transfer Learning AAAI 2021 APQ: Joint Search for Network Architecture, Pruning and Quantization Policy CVPR 2020 ASAP: Architecture Search, Anneal and Prune AISTATS 2020 Dissecting Lottery Ticket Transformers: Structural and Behavioral Study of Sparse Neural Machine Translation EMNLP 2020 Drawing Early-Bird Tickets: Toward More Efficient Training of Deep Networks ICLR 2020 Dynamic Model Pruning with Feedback ICLR 2020 FastFormers: Highly Efficient Transformer Models for Natural Language Understanding EMNLP 2020 Few Sample Knowledge Distillation for Efficient Network Compression CVPR 2020 Few Shot Network Compression via Cross Distillation AAAI 2020 High Performance Natural Language Processing EMNLP 2020 Losing Heads in the Lottery: Pruning Transformer Attention in Neural Machine Translation EMNLP 2020 Movement Pruning: Adaptive Sparsity by Fine-Tuning NeurIPS 2020 Multi-Dimensional Pruning: A Unified Framework for Model Compression CVPR 2020 Neural Epitome Search for Architecture-Agnostic Network Compression ICLR 2020 On the Sparsity of Neural Machine Translation Models EMNLP 2020 On the weak link between importance and prunability of attention heads EMNLP 2020 Position-based Scaled Gradient for Model Quantization and Pruning NeurIPS 2020