data augmentation

Investigations on Data Augmentation and Loss Functions for Deep Learning Based Speech-Background Separation Interspeech 2018 KT-Speech-Crawler: Automatic Dataset Construction for Speech Recognition from YouTube Videos EMNLP 2018 Learning Compositional Visual Concepts With Mutual Consistency CVPR 2018 Learning from Between-class Examples for Deep Sound Recognition ICLR 2018 Learning Invariances using the Marginal Likelihood NeurIPS 2018 Learning Priors for Invariance AISTATS 2018 Learning to Evaluate Image Captioning CVPR 2018 Low-Shot Learning From Imaginary Data CVPR 2018 Low-shot Learning via Covariance-Preserving Adversarial Augmentation Networks NeurIPS 2018 mixup: Beyond Empirical Risk Minimization ICLR 2018 Multi-Modal Data Augmentation for End-to-end ASR Interspeech 2018 Multi-Source Neural Machine Translation with Data Augmentation EMNLP 2018 Multistage Adversarial Losses for Pose-Based Human Image Synthesis CVPR 2018 Noising and Denoising Natural Language: Diverse Backtranslation for Grammar Correction NAACL 2018 OhioState at SemEval-2018 Task 7: Exploiting Data Augmentation for Relation Classification in Scientific Papers Using Piecewise Convolutional Neural Networks SemEval 2018 Pose Transferrable Person Re-Identification CVPR 2018 QANet: Combining Local Convolution with Global Self-Attention for Reading Comprehension ICLR 2018 Reducing Gender Bias in Abusive Language Detection EMNLP 2018 RICAP: Random Image Cropping and Patching Data Augmentation for Deep CNNs ACML 2018 Samsung and University of Edinburgh’s System for the IWSLT 2018 Low Resource MT Task EMNLP 2018 Scaling up Data Augmentation MCMC via Calibration JMLR 2018 Semantically Equivalent Adversarial Rules for Debugging NLP models ACL 2018 Sensitivity and Generalization in Neural Networks: an Empirical Study ICLR 2018 Sequence-to-Sequence Data Augmentation for Dialogue Language Understanding COLING 2018 Sheffield Submissions for WMT18 Multimodal Translation Shared Task EMNLP 2018