| Network embedding as matrix factorization: Unifying deepwalk, line, pte, and node2vec J Qiu, Y Dong, H Ma, J Li, K Wang, J Tang Proceedings of the eleventh ACM international conference on web search and …, 2018 | 1115 | 2018 |
| Brits: Bidirectional recurrent imputation for time series W Cao, D Wang, J Li, H Zhou, L Li, Y Li NeurIPS 2018, 2018 | 815 | 2018 |
| When will you arrive? Estimating travel time based on deep neural networks D Wang, J Zhang, W Cao, J Li, Y Zheng Proceedings of the AAAI conference on artificial intelligence 32 (1), 2018 | 426 | 2018 |
| Gradient descent maximizes the margin of homogeneous neural networks K Lyu, J Li ICLR 2020, 2019 | 359 | 2019 |
| Latent consistency models: Synthesizing high-resolution images with few-step inference S Luo, Y Tan, L Huang, J Li, H Zhao arXiv preprint arXiv:2310.04378, 2023 | 306 | 2023 |
| A unified approach to ranking in probabilistic databases J Li, B Saha, A Deshpande The VLDB Journal 20, 249-275, 2011 | 253 | 2011 |
| DeepSD: Supply-demand prediction for online car-hailing services using deep neural networks D Wang, W Cao, J Li, J Ye 2017 IEEE 33rd international conference on data engineering (ICDE), 243-254, 2017 | 236 | 2017 |
| Netsmf: Large-scale network embedding as sparse matrix factorization J Qiu, Y Dong, H Ma, J Li, C Wang, K Wang, J Tang The World Wide Web Conference, 1509-1520, 2019 | 214 | 2019 |
| Less is more: Fast multivariate time series forecasting with light sampling-oriented mlp structures T Zhang, Y Zhang, W Cao, J Bian, X Yi, S Zheng, J Li arXiv preprint arXiv:2207.01186, 2022 | 171 | 2022 |
| Combinatorial multi-armed bandit with general reward functions W Chen, W Hu, F Li, J Li, Y Liu, P Lu Advances in Neural Information Processing Systems 29, 2016 | 160 | 2016 |
| When LP is the cure for your matching woes: Improved bounds for stochastic matchings N Bansal, A Gupta, J Li, J Mestre, V Nagarajan, A Rudra Algorithmica 63, 733-762, 2012 | 132 | 2012 |
| A simple proximal stochastic gradient method for nonsmooth nonconvex optimization Z Li, J Li NeurIPS 2018, 2018 | 125 | 2018 |
| Learning gradient descent: Better generalization and longer horizons K Lv, S Jiang, J Li International Conference on Machine Learning, 2247-2255, 2017 | 125 | 2017 |
| Optimal PAC multiple arm identification with applications to crowdsourcing Y Zhou, X Chen, J Li International Conference on Machine Learning, 217-225, 2014 | 123 | 2014 |
| Cost-effective crowdsourced entity resolution: A partial-order approach C Chai, G Li, J Li, D Deng, J Feng Proceedings of the 2016 International Conference on Management of Data, 969-984, 2016 | 117 | 2016 |
| Data generation using declarative constraints A Arasu, R Kaushik, J Li Proceedings of the 2011 ACM SIGMOD International Conference on Management of …, 2011 | 117 | 2011 |
| Lcm-lora: A universal stable-diffusion acceleration module S Luo, Y Tan, S Patil, D Gu, P von Platen, A Passos, L Huang, J Li, ... arXiv preprint arXiv:2311.05556, 2023 | 110 | 2023 |
| Lrspeech: Extremely low-resource speech synthesis and recognition J Xu, X Tan, Y Ren, T Qin, J Li, S Zhao, TY Liu Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020 | 101 | 2020 |
| Sensitivity analysis and explanations for robust query evaluation in probabilistic databases B Kanagal, J Li, A Deshpande Proceedings of the 2011 ACM SIGMOD International Conference on Management of …, 2011 | 94 | 2011 |
| Flipda: Effective and robust data augmentation for few-shot learning J Zhou, Y Zheng, J Tang, J Li, Z Yang arXiv preprint arXiv:2108.06332, 2021 | 91 | 2021 |
Amol DeshpandeUniversity of Marylandcs.umd.edu의 이메일 확인됨