| Adversarial attacks on graph neural networks via node injections: A hierarchical reinforcement learning approach Y Sun, S Wang, X Tang, TY Hsieh, V Honavar Proceedings of the Web Conference 2020, 673-683, 2020 | 165 | 2020 |
| Fuzzy integral with particle swarm optimization for a motor-imagery-based brain–computer interface SL Wu, YT Liu, TY Hsieh, YY Lin, CY Chen, CH Chuang, CT Lin IEEE Transactions on Fuzzy Systems 25 (1), 21-28, 2016 | 90 | 2016 |
| Explainable multivariate time series classification: a deep neural network which learns to attend to important variables as well as time intervals TY Hsieh, S Wang, Y Sun, V Honavar Proceedings of the 14th ACM international conference on web search and data …, 2021 | 78 | 2021 |
| Minority oversampling in kernel adaptive subspaces for class imbalanced datasets CT Lin, TY Hsieh, YT Liu, YY Lin, CN Fang, YK Wang, G Yen, NR Pal, ... IEEE Transactions on Knowledge and Data Engineering 30 (5), 950-962, 2017 | 68 | 2017 |
| Min-redundancy and max-relevance multi-view feature selection for predicting ovarian cancer survival using multi-omics data Y El-Manzalawy, TY Hsieh, M Shivakumar, D Kim, V Honavar BMC medical genomics 11, 19-31, 2018 | 58 | 2018 |
| Node injection attacks on graphs via reinforcement learning Y Sun, S Wang, X Tang, TY Hsieh, V Honavar arXiv preprint arXiv:1909.06543, 2019 | 54 | 2019 |
| Megan: A generative adversarial network for multi-view network embedding Y Sun, S Wang, TY Hsieh, X Tang, V Honavar arXiv preprint arXiv:1909.01084, 2019 | 54 | 2019 |
| Non-target-specific node injection attacks on graph neural networks: A hierarchical reinforcement learning approach Y Sun, S Wang, X Tang, TY Hsieh, V Honavar Proc. WWW 3, 2020 | 34 | 2020 |
| Multi-view network embedding via graph factorization clustering and co-regularized multi-view agreement Y Sun, N Bui, TY Hsieh, V Honavar 2018 ieee international conference on data mining workshops (icdmw), 1006-1013, 2018 | 21 | 2018 |
| Adaptive structural co-regularization for unsupervised multi-view feature selection TY Hsieh, Y Sun, S Wang, V Honavar 2019 IEEE International Conference on Big Knowledge (ICBK), 87-96, 2019 | 11 | 2019 |
| SrVARM: State regularized vector autoregressive model for joint learning of hidden state transitions and state-dependent inter-variable dependencies from multi-variate time series TY Hsieh, Y Sun, X Tang, S Wang, VG Honavar Proceedings of the Web Conference 2021, 2270-2280, 2021 | 9 | 2021 |
| Functional autoencoders for functional data representation learning TY Hsieh, Y Sun, S Wang, V Honavar Proceedings of the 2021 SIAM International Conference on Data Mining (SDM …, 2021 | 9 | 2021 |
| Assessment of mental fatigue: an EEG-based forecasting system for driving safety YT Liu, YY Lin, SL Wu, TY Hsieh, CT Lin 2015 IEEE International Conference on Systems, Man, and Cybernetics, 3233-3238, 2015 | 8 | 2015 |
| Developing a novel multi-fusion brain-computer interface (BCI) system with particle swarm optimization for motor imagery task TY Hsieh, YY Lin, YT Liu, CN Fang, CT Lin 2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 1-4, 2015 | 6 | 2015 |
| A novel mechanism to fuse various sub-aspect brain-computer interface (BCI) systems with PSO for motor imagery task CT Lin, TY Hsieh, YT Liu, SL Wu, YY Lin 2015 IEEE International Conference on Systems, Man, and Cybernetics, 3223-3228, 2015 | 4 | 2015 |
| An adaptive subspace self-organizing map (assom) imbalanced learning and its applications in eeg CT Lin, YT Liu, CH Chuang, NR Pal, YY Lin, TY Hsieh, CN Fan, Z Cao arXiv preprint arXiv:1906.02772, 2019 | 2 | 2019 |
| Adaptive subspace sampling for class imbalance processing YT Liu, NR Pal, SL Wu, TY Hsieh, CT Lin 2016 International Conference on Fuzzy Theory and Its Applications (iFuzzy), 1-5, 2016 | 2 | 2016 |
| Adaptive Subspace Sampling for Class Imbalance Processing-Some clarifications, algorithm, and further investigation including applications to Brain Computer Interface CT Lin, KC Huang, NR Pal, Z Cao, YT Liu, CN Fang, TY Hsieh, YY Lin, ... 2020 International Conference on Fuzzy Theory and Its Applications (iFUZZY), 1-8, 2020 | 1 | 2020 |
| Compositional stochastic average gradient for machine learning and related applications TY Hsieh, Y El-Manzalawy, Y Sun, V Honavar Intelligent Data Engineering and Automated Learning–IDEAL 2018: 19th …, 2018 | 1 | 2018 |
| Explainable Predictive Modeling and Causal Effect Estimation from Complex Time-Varying Data TY Hsieh The Pennsylvania State University, 2021 | | 2021 |
Vasant G HonavarDorothy Foehr Huck and J. Lloyd Huck Chair in Biomedical Data Sciences and Artificial Intelligence在 psu.edu 的电子邮件经过验证
