← Learning Types
Machine Learning › Learning Types ›

Self-Supervised Learning

8255 directly classified papers

Papers per year

Papers

Meaning to Form: Measuring Systematicity as Information ACL 2019
QAInfomax: Learning Robust Question Answering System by Mutual Information Maximization IJCNLP 2019
Which Ones Are Speaking? Speaker-Inferred Model for Multi-Talker Speech Separation INTERSPEECH 2019
Direct Modelling of Speech Emotion from Raw Speech INTERSPEECH 2019
Concept Pointer Network for Abstractive Summarization EMNLP 2019
UER: An Open-Source Toolkit for Pre-training Models EMNLP 2019
Neural Text Simplification of Clinical Letters with a Domain Specific Phrase Table ACL 2019
RANet: Ranking Attention Network for Fast Video Object Segmentation ICCV 2019
3D Local Features for Direct Pairwise Registration CVPR 2019
Recursive Context-Aware Lexical Simplification IJCNLP 2019
Interactive Sketch & Fill: Multiclass Sketch-to-Image Translation ICCV 2019
BrainEE at SemEval-2019 Task 3: Ensembling Linear Classifiers for Emotion Prediction SEMEVAL 2019
Yimmon at SemEval-2019 Task 9: Suggestion Mining with Hybrid Augmented Approaches SEMEVAL 2019
Multi-Team: A Multi-attention, Multi-decoder Approach to Morphological Analysis. ACL 2019
BERT-based Lexical Substitution ACL 2019
Learning to Speak and Act in a Fantasy Text Adventure Game IJCNLP 2019
Two Generator Game: Learning to Sample via Linear Goodness-of-Fit Test NIPS 2019
Combining Generative and Discriminative Models for Hybrid Inference NIPS 2019
Unsupervised Neural Machine Translation with Future Rewarding CONLL 2019
Generative Well-intentioned Networks NIPS 2019
Controllable Unsupervised Text Attribute Transfer via Editing Entangled Latent Representation NIPS 2019
Latent Suicide Risk Detection on Microblog via Suicide-Oriented Word Embeddings and Layered Attention IJCNLP 2019
EGG: a toolkit for research on Emergence of lanGuage in Games IJCNLP 2019
Countering the Effects of Lead Bias in News Summarization via Multi-Stage Training and Auxiliary Losses EMNLP 2019
Self-Paced Multi-Label Learning with Diversity ACML 2019