| Optimization methods for designing sequences with low autocorrelation sidelobes J Song, P Babu, DP Palomar IEEE Transactions on Signal Processing 63 (15), 3998-4009, 2015 | 368 | 2015 |
| Deepseekmath: Pushing the limits of mathematical reasoning in open language models Z Shao, P Wang, Q Zhu, R Xu, J Song, X Bi, H Zhang, M Zhang, YK Li, ... arXiv preprint arXiv:2402.03300, 2024 | 310* | 2024 |
| Sequence design to minimize the weighted integrated and peak sidelobe levels J Song, P Babu, DP Palomar IEEE Transactions on Signal Processing 64 (8), 2051-2064, 2015 | 298 | 2015 |
| Deepseek-r1: Incentivizing reasoning capability in llms via reinforcement learning D Guo, D Yang, H Zhang, J Song, R Zhang, R Xu, Q Zhu, S Ma, P Wang, ... arXiv preprint arXiv:2501.12948, 2025 | 238 | 2025 |
| Deepseek llm: Scaling open-source language models with longtermism X Bi, D Chen, G Chen, S Chen, D Dai, C Deng, H Ding, K Dong, Q Du, ... arXiv preprint arXiv:2401.02954, 2024 | 235 | 2024 |
| Sequence set design with good correlation properties via majorization-minimization J Song, P Babu, DP Palomar IEEE Transactions on Signal Processing 64 (11), 2866-2879, 2016 | 219 | 2016 |
| Deepseek-v3 technical report A Liu, B Feng, B Xue, B Wang, B Wu, C Lu, C Zhao, C Deng, C Zhang, ... arXiv preprint arXiv:2412.19437, 2024 | 175 | 2024 |
| Deepseek-coder-v2: Breaking the barrier of closed-source models in code intelligence Q Zhu, D Guo, Z Shao, D Yang, P Wang, R Xu, Y Wu, Y Li, H Gao, S Ma, ... arXiv preprint arXiv:2406.11931, 2024 | 170* | 2024 |
| A unified framework for low autocorrelation sequence design via majorization–minimization L Zhao, J Song, P Babu, DP Palomar IEEE Transactions on Signal Processing 65 (2), 438-453, 2016 | 162 | 2016 |
| Deepseek-v2: A strong, economical, and efficient mixture-of-experts language model A Liu, B Feng, B Wang, B Wang, B Liu, C Zhao, C Dengr, C Ruan, D Dai, ... arXiv preprint arXiv:2405.04434, 2024 | 141 | 2024 |
| Sparse generalized eigenvalue problem via smooth optimization J Song, P Babu, DP Palomar IEEE Transactions on Signal Processing 63 (7), 1627-1642, 2015 | 78 | 2015 |
| SCC: an efficient deep reinforcement learning agent mastering the game of StarCraft II X Wang, J Song, P Qi, P Peng, Z Tang, W Zhang, W Li, X Pi, J He, C Gao, ... International Conference on Machine Learning, 10905-10915, 2021 | 62* | 2021 |
| Deepseek-prover-v1. 5: Harnessing proof assistant feedback for reinforcement learning and monte-carlo tree search H Xin, ZZ Ren, J Song, Z Shao, W Zhao, H Wang, B Liu, L Zhang, X Lu, ... arXiv preprint arXiv:2408.08152, 2024 | 34* | 2024 |
| Universal binary semidefinite relaxation for ML signal detection X Fan, J Song, DP Palomar, OC Au IEEE transactions on communications 61 (11), 4565-4576, 2013 | 18 | 2013 |
| Sequence design to minimize the peak sidelobe level J Song, P Babu, DP Palomar 2016 IEEE International Conference on Acoustics, Speech and Signal …, 2016 | 12 | 2016 |
| Optimization methods for sequence design with low autocorrelation sidelobes J Song, P Babu, DP Palomar 2015 IEEE International Conference on Acoustics, Speech and Signal …, 2015 | 10 | 2015 |
| AlphaZero-Gomoku J Song https://github.com/junxiaosong/AlphaZero_Gomoku, 2018 | 4 | 2018 |
| Harnessing Proof Assistant Feedback for Reinforcement Learning and Monte-Carlo Tree Search H Xin, ZZ Ren, J Song, Z Shao, W Zhao, H Wang, B Liu, L Zhang, X Lu, ... The Thirteenth International Conference on Learning Representations, 0 | | |
Daniel P. PalomarDepartment of Electronic & Computer Engineering, Department of Industrial Eng. & Decision AnalyticsПотвърден имейл адрес: ust.hk