sparse model

Sparse Mixers: Combining MoE and Mixing to build a more efficient BERT EMNLP 2022 Sparse Non-Local CRF CVPR 2022 The Optimal BERT Surgeon: Scalable and Accurate Second-Order Pruning for Large Language Models EMNLP 2022 Tricks for Training Sparse Translation Models NAACL 2022 Who Says Elephants Can’t Run: Bringing Large Scale MoE Models into Cloud Scale Production EMNLP 2022 BASE Layers: Simplifying Training of Large, Sparse Models ICML 2021 Beyond Distillation: Task-level Mixture-of-Experts for Efficient Inference EMNLP 2021 Leveraging Sparse Linear Layers for Debuggable Deep Networks ICML 2021 Provable Benefits of Overparameterization in Model Compression: From Double Descent to Pruning Neural Networks AAAI 2021 Dual Extrapolation for Sparse GLMs JMLR 2020 Dynamic Model Pruning with Feedback ICLR 2020 Is Pruning Compression?: Investigating Pruning Via Network Layer Similarity WACV 2020 Naive Feature Selection: Sparsity in Naive Bayes AISTATS 2020 One-Size-Fits-All Multilingual Models ACL 2020 On the Sparsity of Neural Machine Translation Models EMNLP 2020 Semismooth Newton Algorithm for Efficient Projections onto ℓ_1, ∞-norm Ball ICML 2020 Successfully Applying the Stabilized Lottery Ticket Hypothesis to the Transformer Architecture ACL 2020 Balanced Sparsity for Efficient DNN Inference on GPU AAAI 2019 IT–IST at the SIGMORPHON 2019 Shared Task: Sparse Two-headed Models for Inflection ACL 2019 Learning Optimized Risk Scores JMLR 2019 Stochastic Iterative Hard Thresholding for Graph-structured Sparsity Optimization ICML 2019 A Tight Bound of Hard Thresholding JMLR 2018 Efficient Sparse-Winograd Convolutional Neural Networks ICLR 2018 Orthogonal Matching Pursuit for Text Classification EMNLP 2018 Localized Lasso for High-Dimensional Regression AISTATS 2017