| Dilated recurrent neural networks S Chang, Y Zhang, W Han, M Yu, X Guo, W Tan, X Cui, M Witbrock, ... Advances in neural information processing systems 30, 2017 | 228 | 2017 |
| Autovc: Zero-shot voice style transfer with only autoencoder loss K Qian, Y Zhang, S Chang, X Yang, M Hasegawa-Johnson International Conference on Machine Learning, 5210-5219, 2019 | 215 | 2019 |
| Streaming recommender systems S Chang, Y Zhang, J Tang, D Yin, Y Chang, MA Hasegawa-Johnson, ... Proceedings of the 26th international conference on world wide web, 381-389, 2017 | 173 | 2017 |
| The lottery ticket hypothesis for pre-trained bert networks T Chen, J Frankle, S Chang, S Liu, Y Zhang, Z Wang, M Carbin Advances in neural information processing systems 33, 15834-15846, 2020 | 121 | 2020 |
| Speech Enhancement Using Bayesian Wavenet. K Qian, Y Zhang, S Chang, X Yang, D Florêncio, M Hasegawa-Johnson Interspeech, 2013-2017, 2017 | 81 | 2017 |
| Unsupervised speech decomposition via triple information bottleneck K Qian, Y Zhang, S Chang, M Hasegawa-Johnson, D Cox International Conference on Machine Learning, 7836-7846, 2020 | 76 | 2020 |
| Invariant rationalization S Chang, Y Zhang, M Yu, T Jaakkola International Conference on Machine Learning, 1448-1458, 2020 | 76 | 2020 |
| Rethinking cooperative rationalization: Introspective extraction and complement control M Yu, S Chang, Y Zhang, TS Jaakkola arXiv preprint arXiv:1910.13294, 2019 | 70 | 2019 |
| Fast generation for convolutional autoregressive models P Ramachandran, TL Paine, P Khorrami, M Babaeizadeh, S Chang, ... arXiv preprint arXiv:1704.06001, 2017 | 65 | 2017 |
| Fast wavenet generation algorithm TL Paine, P Khorrami, S Chang, Y Zhang, P Ramachandran, ... arXiv preprint arXiv:1611.09482, 2016 | 58 | 2016 |
| The lottery tickets hypothesis for supervised and self-supervised pre-training in computer vision models T Chen, J Frankle, S Chang, S Liu, Y Zhang, M Carbin, Z Wang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 54 | 2021 |
| Positive-unlabeled learning in streaming networks S Chang, Y Zhang, J Tang, D Yin, Y Chang, MA Hasegawa-Johnson, ... Proceedings of the 22nd ACM SIGKDD international conference on Knowledge …, 2016 | 35 | 2016 |
| A game theoretic approach to class-wise selective rationalization S Chang, Y Zhang, M Yu, T Jaakkola Advances in neural information processing systems 32, 2019 | 30 | 2019 |
| Deep learning based speech beamforming K Qian, Y Zhang, S Chang, X Yang, D Florencio, M Hasegawa-Johnson 2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018 | 30 | 2018 |
| A multidisciplinary approach to designing and evaluating electronic medical record portal messages that support patient self-care D Morrow, M Hasegawa-Johnson, T Huang, W Schuh, RFL Azevedo, ... Journal of biomedical informatics 69, 63-74, 2017 | 26 | 2017 |
| Generating visually aligned sound from videos P Chen, Y Zhang, M Tan, H Xiao, D Huang, C Gan IEEE Transactions on Image Processing 29, 8292-8302, 2020 | 24 | 2020 |
| Geometry-aware traffic flow analysis by detection and tracking H Shi, Z Wang, X Wang, Y Zhang, TS Huang Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 18 | 2018 |
| Grounding Spoken Words in Unlabeled Video. AW Boggust, K Audhkhasi, D Joshi, D Harwath, S Thomas, RS Feris, ... CVPR Workshops 2, 2019 | 16 | 2019 |
| Probabilistic acoustic tube: a probabilistic generative model of speech for speech analysis/synthesis Z Ou, Y Zhang Artificial intelligence and statistics, 841-849, 2012 | 10 | 2012 |
| Parp: Prune, adjust and re-prune for self-supervised speech recognition CIJ Lai, Y Zhang, AH Liu, S Chang, YL Liao, YS Chuang, K Qian, ... Advances in Neural Information Processing Systems 34, 21256-21272, 2021 | 9 | 2021 |
Shiyu ChangUniversity of California, Santa BarbaraVerified email at cs.ucsb.edu
