| Disentangled representation learning for non-parallel text style transfer V John, L Mou, H Bahuleyan, O Vechtomova arXiv preprint arXiv:1808.04339, 2018 | 361 | 2018 |
| A survey of distributed message broker queues V John, X Liu arXiv preprint arXiv:1704.00411, 2017 | 82 | 2017 |
| A survey of neural network techniques for feature extraction from text V John arXiv preprint arXiv:1704.08531, 2017 | 17 | 2017 |
| Generating lyrics with variational autoencoder and multi-modal artist embeddings O Vechtomova, H Bahuleyan, A Ghabussi, V John arXiv preprint arXiv:1812.08318, 2018 | 15 | 2018 |
| Sentiment analysis on financial news headlines using training dataset augmentation V John, O Vechtomova arXiv preprint arXiv:1707.09448, 2017 | 13 | 2017 |
| UWat-Emote at EmoInt-2017: emotion intensity detection using affect clues, sentiment polarity and word embeddings V John, O Vechtomova Proceedings of the 8th Workshop on Computational Approaches to Subjectivity …, 2017 | 4 | 2017 |
| Redynis: traffic-aware dynamic repartitioning for a distributed key-value store V John arXiv preprint arXiv:1703.08425, 2017 | 1 | 2017 |
| Rapid-Rate: A Framework for Semi-supervised Real-time Sentiment Trend Detection in Unstructured Big Data V John arXiv preprint arXiv:1703.08088, 2017 | 1 | 2017 |
| Disentangled Representation Learning for Stylistic Variation in Neural Language Models V John University of Waterloo, 2018 | | 2018 |
| Team Waterloo at the SIGIR e-Commerce Data Challenge. A Ghosh, V John, R Iyer eCOM@ SIGIR, 2018 | | 2018 |
Olga VechtomovaUniversity of Waterloo在 uwaterloo.ca 的电子邮件经过验证
