| On the Origin of Deep Learning H Wang, B Raj arXiv preprint arXiv:1702.07800, 2017 | 174* | 2017 |
| Select-additive learning: Improving generalization in multimodal sentiment analysis H Wang, A Meghawat, LP Morency, EP Xing 2017 IEEE International Conference on Multimedia and Expo (ICME), 949-954, 2017 | 83 | 2017 |
| Learning structure in gene expression data using deep architectures, with an application to gene clustering A Gupta, H Wang, M Ganapathiraju 2015 IEEE International Conference on Bioinformatics and Biomedicine (BIBM …, 2015 | 55 | 2015 |
| Learning robust representations by projecting superficial statistics out H Wang, Z He, ZC Lipton, EP Xing arXiv preprint arXiv:1903.06256, 2019 | 49 | 2019 |
| Deep learning for genomics: A concise overview T Yue, H Wang arXiv preprint arXiv:1802.00810, 2018 | 49 | 2018 |
| High-frequency component helps explain the generalization of convolutional neural networks H Wang, X Wu, Z Huang, EP Xing Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 41 | 2020 |
| Unlearn dataset bias in natural language inference by fitting the residual H He, S Zha, H Wang arXiv preprint arXiv:1908.10763, 2019 | 39 | 2019 |
| Rumor propagation dynamic model based on evolutionary game and anti-rumor Y Xiao, D Chen, S Wei, Q Li, H Wang, M Xu Nonlinear Dynamics 95 (1), 523-539, 2019 | 36 | 2019 |
| Precision lasso: Accounting for correlations and linear dependencies in high-dimensional genomic data H Wang, BJ Lengerich, B Aragam, EP Xing, O Stegle Bioinformatics, 2018 | 36 | 2018 |
| Using EEG to Improve Massive Open Online Courses Feedback Interaction. H Wang, Y Li, X Hu, Y Yang, Z Meng, K Chang AIED Workshops, 2013 | 32 | 2013 |
| Learning robust global representations by penalizing local predictive power H Wang, S Ge, EP Xing, ZC Lipton arXiv preprint arXiv:1905.13549, 2019 | 31 | 2019 |
| Multimodal transfer deep learning for audio visual recognition S Moon, S Kim, H Wang NIPS MMML Workshop, 2015, 2014 | 30* | 2014 |
| 3-HBP: A three-level hidden Bayesian link prediction model in social networks Y Xiao, X Li, H Wang, M Xu, Y Liu IEEE Transactions on Computational Social Systems 5 (2), 430-443, 2018 | 21 | 2018 |
| Discovery of critical nodes in road networks through mining from vehicle trajectories M Xu, J Wu, M Liu, Y Xiao, H Wang, D Hu IEEE Transactions on Intelligent Transportation Systems 20 (2), 583-593, 2018 | 20 | 2018 |
| What if we simply swap the two text fragments? A straightforward yet effective way to test the robustness of methods to confounding signals in nature language inference tasks H Wang, D Sun, EP Xing Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 7136-7143, 2019 | 15* | 2019 |
| Removing Confounding Factors Associated Weights in Deep Neural Networks Improves the Prediction Accuracy for Healthcare Applications H Wang, Z Wu, EP Xing arXiv preprint arXiv:1803.07276, 2018 | 15* | 2018 |
| Multiple Confounders Correction with Regularized Linear Mixed Effect Models with Application in Biological Processes H Wang, J Yang Bioinformatics and Biomedicine (BIBM), 2016 IEEE International Conference on, 2016 | 14 | 2016 |
| Variable selection in heterogeneous datasets: A truncated-rank sparse linear mixed model with applications to genome-wide association studies H Wang, B Aragam, EP Xing 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM …, 2017 | 13 | 2017 |
| Behavior analysis of low-literate users of a viral speech-based telephone service H Wang, AA Raza, Y Lin, R Rosenfeld Proceedings of the 4th Annual Symposium on Computing for Development, 1-9, 2013 | 13 | 2013 |
| Self-challenging improves cross-domain generalization Z Huang, H Wang, EP Xing, D Huang arXiv preprint arXiv:2007.02454 2, 2020 | 9 | 2020 |
Eric XingProfessor of Machine Learning, Language Technology, Computer Science, Cargenie Mellon UniversityVerified email at cs.cmu.edu
