conftrace_
← Optimization & Theory
Deep Learning › Optimization & Theory ›

Model Compression

1,785 papers

Papers per year

7
197
419
'15
'20
'25

Papers

Rank and run-time aware compression of NLP Applications EMNLP 2020
End to End Binarized Neural Networks for Text Classification EMNLP 2020
Exploring the Boundaries of Low-Resource BERT Distillation EMNLP 2020
Efficient Inference For Neural Machine Translation EMNLP 2020
Early Exiting BERT for Efficient Document Ranking EMNLP 2020
Load What You Need: Smaller Versions of Mutililingual BERT EMNLP 2020
SqueezeBERT: What can computer vision teach NLP about efficient neural networks? EMNLP 2020
FastFormers: Highly Efficient Transformer Models for Natural Language Understanding EMNLP 2020
Overview of the SustaiNLP 2020 Shared Task EMNLP 2020
Training Binary Neural Networks through Learning with Noisy Supervision ICML 2020
The Tree Ensemble Layer: Differentiability meets Conditional Computation ICML 2020
Operation-Aware Soft Channel Pruning using Differentiable Masks ICML 2020
Soft Threshold Weight Reparameterization for Learnable Sparsity ICML 2020
Finding trainable sparse networks through Neural Tangent Transfer ICML 2020
Up or Down? Adaptive Rounding for Post-Training Quantization ICML 2020
T-Basis: a Compact Representation for Neural Networks ICML 2020
Multiclass Neural Network Minimization via Tropical Newton Polytope Approximation ICML 2020
The k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks ICML 2020
DropNet: Reducing Neural Network Complexity via Iterative Pruning ICML 2020
Variational Bayesian Quantization ICML 2020
Good Subnetworks Provably Exist: Pruning via Greedy Forward Selection ICML 2020
Channel Pruning via Automatic Structure Search IJCAI 2020
Soft Threshold Ternary Networks IJCAI 2020
Beyond Network Pruning: a Joint Search-and-Training Approach IJCAI 2020
Spectral Pruning: Compressing Deep Neural Networks via Spectral Analysis and its Generalization Error IJCAI 2020