| An adaptive empirical Bayesian method for sparse deep learning W Deng, X Zhang, F Liang, G Lin Advances in neural information processing systems 32, 2019 | 45 | 2019 |
| Semi-supervised structured prediction with neural crf autoencoder X Zhang, Y Jiang, H Peng, K Tu, D Goldwasser EMNLP, 2017 | 36 | 2017 |
| Asynchronous distributed variational Gaussian process for regression H Peng, S Zhe, X Zhang, Y Qi International Conference on Machine Learning, 2788-2797, 2017 | 29 | 2017 |
| Understanding satirical articles using common-sense D Goldwasser, X Zhang Transactions of the Association for Computational Linguistics 4, 537-549, 2016 | 17 | 2016 |
| ACE--An Anomaly Contribution Explainer for Cyber-Security Applications X Zhang, M Marwah, I Lee, M Arlitt, D Goldwasser IEEE Bigdata, 2019 | 13 | 2019 |
| Sentiment tagging with partial labels using modular architectures X Zhang, D Goldwasser ACL, 2019 | 13 | 2019 |
| Introducing drail -- a step towards declarative deep relational learning X Zhang, ML Pacheco, C Li, D Goldwasser Proceedings of the Workshop on Structured Prediction for NLP, 54-62, 2016 | 9 | 2016 |
| Cross-lingual Document Retrieval with Smooth Learning J Liu, X Zhang, D Goldwasser, X Wang COLING, 2020 | 6 | 2020 |
| PurdueNLP at SemEval-2017 Task 1: Predicting semantic textual similarity with paraphrase and event embeddings IT Lee, M Goindani, C Li, D Jin, K Johnson, X Zhang, ML Pacheco, ... Proceedings of the 11th International Workshop on Semantic Evaluation …, 2017 | 6 | 2017 |
| Adapting event embedding for implicit discourse relation recognition ML Pacheco, IT Lee, X Zhang, AK Zehady, P Daga, D Jin, A Parolia, ... Proceedings of the CoNLL-16 shared task, 136-142, 2016 | 5 | 2016 |
| How to optimize switch virtual keyboards to trade off speed and accuracy X Zhang, K Fang, G Francis Cognitive Research: Principles and Implications 1, 1-18, 2016 | 4 | 2016 |
| Optimization of switch keyboards X Zhang, K Fang, G Francis Proceedings of the 15th International ACM SIGACCESS Conference on Computers …, 2013 | 3 | 2013 |
| Semi-supervised Parsing with a Variational Autoencoding Parser X Zhang, D Goldwasser Proceedings of the 16th International Conference on Parsing Technologies and …, 2020 | 2 | 2020 |
| Identification of input features used by machine learning model in providing output score M Marwah, X Zhang, M Arlitt US Patent App. 15/938,624, 2019 | 2 | 2019 |
| Improving Programming Q&A with Neural Generative Augmentation U Suthee, X Zhang, S Subramaniyam, J Svajlenko, T Shourya, ... SIGIR, 2023 | | 2023 |
| MICO: Selective Search with Mutual Information Co-training Z Wang, X Zhang, H Yun, CH Teo, T Chilimbi COLING, 2022 | | 2022 |
| Semi-supervised Autoencoding Projective Dependency Parsing X Zhang, D Goldwasser COLING, 2020 | | 2020 |
| Rademacher Complexity of the Restricted Boltzmann Machine X Zhang arXiv preprint arXiv:1512.01914, 2015 | | 2015 |
| OPTIMIZATION OF SWITCH VIRTUAL KEYBOARD XC Zhang Purdue University West Lafayette, 2014 | | 2014 |
| How Can Computational HCI Assist Experimental HCI: Designing an Optimized Keyboard for People in Motor-Control Difficulties XC Zhang | | 2014 |
Dan GoldwasserPurdue UniversityZweryfikowany adres z purdue.edu
