← Techniques
Deep Learning › Techniques ›

Knowledge Distillation

623 directly classified papers

Papers per year

Papers

Structured Pruning of Neural Networks With Budget-Aware Regularization CVPR 2019
MBS: Macroblock Scaling for CNN Model Reduction CVPR 2019
Variational Information Distillation for Knowledge Transfer CVPR 2019
Amalgamating Knowledge towards Comprehensive Classification AAAI 2019
Towards Architecture-Agnostic Neural Transfer: a Knowledge-Enhanced Approach IJCAI 2019
Baidu Neural Machine Translation Systems for WMT19 ACL 2019
Scalable Syntax-Aware Language Models Using Knowledge Distillation ACL 2019
Zero-Shot Cross-Lingual Abstractive Sentence Summarization through Teaching Generation and Attention ACL 2019
Network Recasting: A Universal Method for Network Architecture Transformation AAAI 2019
Training Deep Neural Networks in Generations: A More Tolerant Teacher Educates Better Students AAAI 2019
Boosting Self-Supervised Learning via Knowledge Transfer CVPR 2018
Marian: Cost-effective High-Quality Neural Machine Translation in C++ ACL 2018
WSNet: Compact and Efficient Networks Through Weight Sampling ICML 2018
Knowledge Distillation for Sequence Model INTERSPEECH 2018
Sobolev Training for Neural Networks NIPS 2017
Transfer Learning and Distillation Techniques to Improve the Acoustic Modeling of Low Resource Languages INTERSPEECH 2017
Knowledge Distillation for Bilingual Dictionary Induction EMNLP 2017
Mimicking Very Efficient Network for Object Detection CVPR 2017
Student-Teacher Training with Diverse Decision Tree Ensembles INTERSPEECH 2017
Efficient Knowledge Distillation from an Ensemble of Teachers INTERSPEECH 2017
A Teacher-Student Framework for Zero-Resource Neural Machine Translation ACL 2017
Real-Time Action Recognition With Enhanced Motion Vector CNNs CVPR 2016
Do Deep Nets Really Need to be Deep? NIPS 2014