| Fengshenbang 1.0: Being the foundation of chinese cognitive intelligence J Zhang, R Gan, J Wang, Y Zhang, L Zhang, P Yang, X Gao, Z Wu, ... arXiv preprint arXiv:2209.02970, 2022 | 81 | 2022 |
| Solving Math Word Problem via Cooperative Reasoning induced Language Models X Zhu, J Wang, L Zhang, Y Zhang, R Gan, J Zhang, Y Yang Annual Meeting of the Association for Computational Linguistics (ACL). 2023, 2022 | 36 | 2022 |
| M-Track: a new software for automated detection of grooming trajectories in mice R SL, F KE, Z L, S A. PLoS Comput Biol 12 (9), 2016 | 31 | 2016 |
| Zero-Shot Learners for Natural Language Understanding via a Unified Multiple Choice Perspective P Yang, J Wang, R Gan, X Zhu, L Zhang, Z Wu, X Gao, J Zhang, T Sakai Empirical Methods in Natural Language Processing (EMNLP), 2022 | 15 | 2022 |
| PERCeIDs: Periodic Community Detection L Zhang, A Gorovits, P Bogdanov. IEEE International Conference on Data Mining (ICDM), 2019 | 12 | 2019 |
| An Efficient Approach for Cell Segmentation in Phase Contrast Microscopy Images L Zhang arXiv preprint arXiv:1904.00328, 2017 | 9 | 2017 |
| Feature Expansion for Graph Neural Networks J Sun, L Zhang, G Chen, K Zhang, P XU, Y Yang International Conference on Machine Learning (ICML) 2023, 2023 | 8 | 2023 |
| Temporal graph signal decomposition MJ McNeil, L Zhang, P Bogdanov Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data …, 2021 | 8 | 2021 |
| Mvp-tuning: Multi-view knowledge retrieval with prompt tuning for commonsense reasoning Y Huang, Y Li, Y Xu, L Zhang, R Gan, J Zhang, L Wang Proceedings of the 61st Annual Meeting of the Association for Computational …, 2023 | 6 | 2023 |
| MAP: Modality-Agnostic Uncertainty-Aware Vision-Language Pre-training Model Y Ji, J Wang, Y Gong, L Zhang, Y Zhu, H Wang, J Zhang, T Sakai, Y Yang The IEEE / CVF Computer Vision and Pattern Recognition Conference (CVPR), 2023 | 6 | 2023 |
| Learning Periods from Incomplete Multivariate Time Series L Zhang, A Gorovits, W Zhang, P Bogdanov. IEEE International Conference on Data Mining (ICDM), 2020 | 5 | 2020 |
| DSL: discriminative subgraph learning via sparse self-representation L Zhang, P Bogdanov Proceedings of the 2019 SIAM International Conference on Data Mining, 333-341, 2019 | 5 | 2019 |
| Improving Your Graph Neural Networks: A High-Frequency Booster J Sun, L Zhang, S Zhao, Y Yang IEEE International Conference on Data Mining, 2022 | 4 | 2022 |
| Exploiting Self-Similarity for Under-Determined MIMO Modulation Recognition. W Xiong, L Zhang, MJ McNeil, P Bogdanov, M Zheleva. IEEE International Conference on Computer Communications, 2020 | 4 | 2020 |
| Mining bursty groups from interaction data A Gorovits, L Zhang, E Gujral, E Papalexakis, P Bogdanov Proceedings of the 30th ACM International Conference on Information …, 2021 | 3 | 2021 |
| : Exploiting MIMO Self-Similarity for Under-Determined Modulation Recognition W Xiong, L Zhang, M McNeil, P Bogdanov, M Zheleva IEEE Transactions on Mobile Computing 21 (11), 4111-4124, 2021 | 3 | 2021 |
| Do Not Train It: A Linear Neural Architecture Search of Graph Neural Networks P Xu, L Zhang, X Liu, J Sun, Y Zhao, H Yang, B Yu International Conference on Machine Learning (ICML), 2023 | 2 | 2023 |
| A Large-scale Friend Suggestion Architecture L Zhang, R Li. IEEE International Conference on Data Science and Advanced Analytics, 2022 | 2 | 2022 |
| AURORA: A Unified fRamework fOR Anomaly detection on multivariate time series. L Zhang, W Zhang, MJ McNeil, N Chengwang, DS Matteson, P Bogdanov The European Conference on Machine Learning and Principles and Practice of …, 2020 | 2 | 2020 |
| Period Estimation For Incomplete Time Series. L Zhang, P Bogdanov. IEEE International Conference on Data Science and Advanced Analytics (DSAA), 2020 | 2 | 2020 |
Petko BogdanovUniversity at Albany-SUNYVerified email at albany.edu
