← Application Areas
Machine Learning › Application Areas ›

Data Augmentation

3622 directly classified papers

Papers per year

Papers

Towards Scale-Free Rain Streak Removal via Self-Supervised Fractal Band Learning AAAI 2020
Tell Me How to Ask Again: Question Data Augmentation with Controllable Rewriting in Continuous Space EMNLP 2020
Improving Auto-Augment via Augmentation-Wise Weight Sharing NIPS 2020
VFlow: More Expressive Generative Flows with Variational Data Augmentation ICML 2020
Iterative Feature Mining for Constraint-Based Data Collection to Increase Data Diversity and Model Robustness EMNLP 2020
Hard Negative Mixing for Contrastive Learning NIPS 2020
High-contrast “gaudy” images improve the training of deep neural network models of visual cortex NIPS 2020
Parallel resources for Tunisian Arabic Dialect Translation COLING 2020
Synthetic Examples Improve Generalization for Rare Classes WACV 2020
Auxiliary Task Reweighting for Minimum-data Learning NIPS 2020
Rethinking Pre-training and Self-training NIPS 2020
FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence NIPS 2020
Affective Event Classification with Discourse-enhanced Self-training EMNLP 2020
PATQUEST: Papago Translation Quality Estimation EMNLP 2020
Meta Variance Transfer: Learning to Augment from the Others ICML 2020
Machine Translation for English–Inuktitut with Segmentation, Data Acquisition and Pre-Training EMNLP 2020
Optimizing Millions of Hyperparameters by Implicit Differentiation AISTATS 2020
Leveraging BERT with Mixup for Sentence Classification (Student Abstract) AAAI 2020
Using Multiple Subwords to Improve English-Esperanto Automated Literary Translation Quality AACL 2020
Noising Scheme for Data Augmentation in Automatic Post-Editing EMNLP 2020
Learning Augmentation Network via Influence Functions CVPR 2020
The LMU Munich System for the WMT20 Very Low Resource Supervised MT Task EMNLP 2020
Synbols: Probing Learning Algorithms with Synthetic Datasets NIPS 2020
Visual Imitation Made Easy CORL 2020
Data Boost: Text Data Augmentation Through Reinforcement Learning Guided Conditional Generation EMNLP 2020