← Optimization & Theory
Deep Learning › Optimization & Theory ›

Model Compression

1674 directly classified papers

Papers per year

Papers

HAWQ-V3: Dyadic Neural Network Quantization ICML 2021
Accelerate CNNs from Three Dimensions: A Comprehensive Pruning Framework ICML 2021
Exploring Sparsity in Image Super-Resolution for Efficient Inference CVPR 2021
Bi-GCN: Binary Graph Convolutional Network CVPR 2021
MobileDets: Searching for Object Detection Architectures for Mobile Accelerators CVPR 2021
Pruning Neural Machine Translation for Speed Using Group Lasso EMNLP 2021
UnClE: Explicitly Leveraging Semantic Similarity to Reduce the Parameters of Word Embeddings EMNLP 2021
How to Train BERT with an Academic Budget EMNLP 2021
Understanding and Overcoming the Challenges of Efficient Transformer Quantization EMNLP 2021
Ultra-High Dimensional Sparse Representations with Binarization for Efficient Text Retrieval EMNLP 2021
Multi-split Reversible Transformers Can Enhance Neural Machine Translation EACL 2021
An Efficient Transformer Decoder with Compressed Sub-layers AAAI 2021
Meta-KD: A Meta Knowledge Distillation Framework for Language Model Compression across Domains ACL 2021
Block-wise Word Embedding Compression Revisited: Better Weighting and Structuring EMNLP 2021
The Low-Resource Double Bind: An Empirical Study of Pruning for Low-Resource Machine Translation EMNLP 2021
Beyond Preserved Accuracy: Evaluating Loyalty and Robustness of BERT Compression EMNLP 2021
Finetuning Pretrained Transformers into RNNs EMNLP 2021
Chasing Sparsity in Vision Transformers: An End-to-End Exploration NIPS 2021
RED : Looking for Redundancies for Data-FreeStructured Compression of Deep Neural Networks NIPS 2021
DeepReduce: A Sparse-tensor Communication Framework for Federated Deep Learning NIPS 2021
PARP: Prune, Adjust and Re-Prune for Self-Supervised Speech Recognition NIPS 2021
Sparse Flows: Pruning Continuous-depth Models NIPS 2021
The Flip Side of the Reweighted Coin: Duality of Adaptive Dropout and Regularization NIPS 2021
Efficient Combination of Rematerialization and Offloading for Training DNNs NIPS 2021
CHIP: CHannel Independence-based Pruning for Compact Neural Networks NIPS 2021