| Inferring Phylogenetic Networks Using PhyloNet D Wen, Y Yun, J Zhu, L Nakhleh Systematic Biology, 2018 | 261 | 2018 |
| Coestimating Reticulate Phylogenies and Gene Trees from Multilocus Sequence Data D Wen, L Nakhleh Systematic Biology, 2017 | 138 | 2017 |
| Software-hardware co-design for fast and scalable training of deep learning recommendation models D Mudigere, Y Hao, J Huang, Z Jia, A Tulloch, S Sridharan, X Liu, ... Proceedings of the 49th Annual International Symposium on Computer …, 2022 | 129* | 2022 |
| Bayesian inference of reticulate phylogenies under the multispecies network coalescent D Wen, Y Yu, L Nakhleh PLoS genetics 12 (5), e1006006, 2016 | 121 | 2016 |
| Reticulate evolutionary history and extensive introgression in mosquito species revealed by phylogenetic network analysis D Wen, Y Yu, MW Hahn, L Nakhleh Molecular Ecology, 2016 | 117 | 2016 |
| Complete decoding of TAL effectors for DNA recognition J Yang, Y Zhang, P Yuan, Y Zhou, C Cai, Q Ren, D Wen, C Chu, H Qi, ... Cell research 24 (5), 628-631, 2014 | 83 | 2014 |
| Bayesian inference of phylogenetic networks from bi-allelic genetic markers J Zhu, D Wen, Y Yu, HM Meudt, L Nakhleh PLoS computational biology 14 (1), e1005932, 2018 | 69 | 2018 |
| ULtiMATE system for rapid assembly of customized TAL effectors J Yang, P Yuan, D Wen, Y Sheng, S Zhu, Y Yu, X Gao, W Wei PLoS One 8 (9), e75649, 2013 | 41 | 2013 |
| A formalized design process for bacterial consortia that perform logic computing W Ji, H Shi, H Zhang, R Sun, J Xi, D Wen, J Feng, Y Chen, X Qin, Y Ma, ... PLoS One 8 (2), e57482, 2013 | 35 | 2013 |
| DHEN: A deep and hierarchical ensemble network for large-scale click-through rate prediction B Zhang, L Luo, X Liu, J Li, Z Chen, W Zhang, X Wei, Y Hao, M Tsang, ... arXiv preprint arXiv:2203.11014, 2022 | 11 | 2022 |
| Low-precision hardware architectures meet recommendation model inference at scale Z Deng, J Park, PTP Tang, H Liu, J Yang, H Yuen, J Huang, D Khudia, ... IEEE Micro 41 (5), 93-100, 2021 | 10 | 2021 |
| Adaptive dense-to-sparse paradigm for pruning online recommendation system with non-stationary data M Ye, D Choudhary, J Yu, E Wen, Z Chen, J Yang, J Park, Q Liu, ... arXiv preprint arXiv:2010.08655, 2020 | 6 | 2020 |
| Towards the Better Ranking Consistency: A Multi-task Learning Framework for Early Stage Ads Ranking X Wang, Q Jin, S Huang, M Zhang, X Liu, Z Zhao, Y Chen, Z Zhang, ... arXiv preprint arXiv:2307.11096, 2023 | 1 | 2023 |
| {AdaEmbed}: Adaptive Embedding for {Large-Scale} Recommendation Models F Lai, W Zhang, R Liu, W Tsai, X Wei, Y Hu, S Devkota, J Huang, J Park, ... 17th USENIX Symposium on Operating Systems Design and Implementation (OSDI …, 2023 | 1 | 2023 |
| Wukong: Towards a Scaling Law for Large-Scale Recommendation B Zhang, L Luo, Y Chen, J Nie, X Liu, D Guo, Y Zhao, S Li, Y Hao, Y Yao, ... arXiv preprint arXiv:2403.02545, 2024 | | 2024 |
| Disaggregated Multi-Tower: Topology-aware Modeling Technique for Efficient Large-Scale Recommendation L Luo, B Zhang, M Tsang, Y Ma, CH Chu, Y Chen, S Li, Y Hao, Y Zhao, ... arXiv preprint arXiv:2403.00877, 2024 | | 2024 |
| {QuickUpdate}: a {Real-Time} Personalization System for {Large-Scale} Recommendation Models KK Matam, H Ramezani, F Wang, Z Chen, Y Dong, M Ding, Z Zhao, ... 21st USENIX Symposium on Networked Systems Design and Implementation (NSDI …, 2024 | | 2024 |
