| Guarantees for Greedy Maximization of Non-submodular Functions with Applications AA Bian, JM Buhmann, A Krause, S Tschiatschek ICML 2017, 2017 | 182 | 2017 |
| Self-Supervised Graph Transformer on Large-Scale Molecular Data Y Rong*, Y Bian*, T Xu, W Xie, Y Wei, W Huang, J Huang Advances in Neural Information Processing Systems 33, 2020 | 151 | 2020 |
| Guaranteed non-convex optimization: Submodular maximization over continuous domains AA Bian, B Mirzasoleiman, JM Buhmann, A Krause AISTATS 2017, 2017 | 112 | 2017 |
| CoLa: Communication-Efficient Decentralized Linear Learning L He*, A Bian*, M Jaggi NeurIPS 2018, 2018 | 92* | 2018 |
| Continuous DR-submodular Maximization: Structure and Algorithms A Bian, K Levy, A Krause, JM Buhmann NIPS 2017, 486-496, 2017 | 55 | 2017 |
| Graph Information Bottleneck for Subgraph Recognition J Yu, T Xu, Y Rong, Y Bian, J Huang, R He ICLR 2021, 2020 | 29 | 2020 |
| Optimal Continuous DR-Submodular Maximization and Applications to Provable Mean Field Inference YA Bian, JM Buhmann, A Krause ICML, 644-653, 2019 | 27* | 2019 |
| A Distributed Second-Order Algorithm You Can Trust C Dünner, A Lucchi, M Gargiani, A Bian, T Hofmann, M Jaggi ICML 2018, 2018 | 27 | 2018 |
| Cross-dependent graph neural networks for molecular property prediction H Ma, Y Bian, Y Rong, W Huang, T Xu, W Xie, G Ye, J Huang Bioinformatics 38 (7), 2003-2009, 2022 | 26* | 2022 |
| Independent SE (3)-Equivariant Models for End-to-End Rigid Protein Docking OE Ganea, X Huang, C Bunne, Y Bian, R Barzilay, T Jaakkola, A Krause ICLR 2022 Spotlight, 2021 | 14 | 2021 |
| Recognizing Predictive Substructures with Subgraph Information Bottleneck J Yu, T Xu, Y Rong, Y Bian, J Huang, R He IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021 | 12 | 2021 |
| Model selection for gaussian process regression NS Gorbach, AA Bian, B Fischer, S Bauer, JM Buhmann German Conference on Pattern Recognition, 306-318, 2017 | 12 | 2017 |
| Parallel Coordinate Descent Newton Method for Efficient -Regularized Loss Minimization YA Bian, X Li, Y Liu, MH Yang IEEE transactions on neural networks and learning systems 30 (11), 3233-3245, 2019 | 10* | 2019 |
| On Self-Distilling Graph Neural Network Y Chen, Y Bian, X Xiao, Y Rong, T Xu, J Huang IJCAI 2021, 2020 | 9 | 2020 |
| Continuous submodular function maximization Y Bian, JM Buhmann, A Krause arXiv preprint arXiv:2006.13474, 2020 | 9 | 2020 |
| Model selection for Gaussian process regression by approximation set coding B Fischer, N Gorbach, S Bauer, Y Bian, JM Buhmann arXiv preprint arXiv:1610.00907, 2016 | 9 | 2016 |
| Greedy maxcut algorithms and their information content Y Bian, A Gronskiy, JM Buhmann 2015 IEEE Information Theory Workshop (ITW), 1-5, 2015 | 8 | 2015 |
| Bundle CDN: A Highly Parallelized Approach for Large-Scale ℓ1-Regularized Logistic Regression Y Bian, X Li, M Cao, Y Liu Joint European Conference on Machine Learning and Knowledge Discovery in …, 2013 | 8 | 2013 |
| DrugOOD: Out-of-Distribution (OOD) Dataset Curator and Benchmark for AI-aided Drug Discovery--A Focus on Affinity Prediction Problems with Noise Annotations Y Ji, L Zhang, J Wu, B Wu, LK Huang, T Xu, Y Rong, L Li, J Ren, D Xue, ... arXiv preprint arXiv:2201.09637, 2022 | 7 | 2022 |
| Parallel Coordinate Descent Newton for Efficient L1-Regularized Minimization Y Bian, X Li, Y Liu, MH Yang arXiv preprint arXiv:1306.4080, 2013 | 6* | 2013 |
Junzhou HuangProfessor of Computer Science and Engineering at the University of Texas at ArlingtonVerified email at uta.edu
