| Online learning for multivariate Hawkes processes Y Yang, J Etesami, N He, N Kiyavash Advances in Neural Information Processing Systems 30, 2017 | 66 | 2017 |
| Prospect pricing in cognitive radio networks Y Yang, LT Park, NB Mandayam, I Seskar, AL Glass, N Sinha IEEE Transactions on Cognitive Communications and Networking 1 (1), 56-70, 2015 | 50 | 2015 |
| A low-complexity cross-layer algorithm for coordinated downlink scheduling and robust beamforming under a limited feedback constraint Y Yang, B Bai, W Chen, L Hanzo IEEE Transactions on Vehicular Technology 63 (1), 107-118, 2014 | 25 | 2014 |
| Learning positive functions with pseudo mirror descent Y Yang, H Wang, N Kiyavash, N He Advances in Neural Information Processing Systems 32, 2019 | 11 | 2019 |
| Impact of end-user decisions on pricing in wireless networks Y Yang, NB Mandayam 2014 48th Annual Conference on Information Sciences and Systems (CISS), 1-6, 2014 | 10 | 2014 |
| Nonparametric Hawkes processes: Online estimation and generalization bounds Y Yang, J Etesami, N He, N Kiyavash arXiv preprint arXiv:1801.08273, 2018 | 9 | 2018 |
| The devil is in the detail: A framework for macroscopic prediction via microscopic models Y Yang, N Kiyavash, L Song, N He Advances in Neural Information Processing Systems 33, 8006-8016, 2020 | 6 | 2020 |
| Predictive approximate Bayesian computation via saddle points Y Yang, B Dai, N Kiyavash, N He Advances in Neural Information Processing Systems 31, 2018 | 6 | 2018 |
| Let models speak ciphers: Multiagent debate through embeddings C Pham, B Liu, Y Yang, Z Chen, T Liu, J Yuan, B Plummer, Z Wang, ... arXiv preprint arXiv:2310.06272, 2023 | 5 | 2023 |
| Impact of end-user decisions on pricing in wireless networks under a multiple-user-single-provider setting Y Yang, NB Mandayam 2014 52nd Annual Allerton Conference on Communication, Control, and …, 2014 | 5 | 2014 |
| Reason out your layout: Evoking the layout master from large language models for text-to-image synthesis X Chen, Y Liu, Y Yang, J Yuan, Q You, LP Liu, H Yang arXiv preprint arXiv:2311.17126, 2023 | 4 | 2023 |
| Detecting nonlinear causality in multivariate time series with sparse additive models Y Yang, AW Yu, Z Wang, T Zhao arXiv preprint arXiv:1803.03919, 2018 | 3 | 2018 |
| Efficient neighborhood selection for Gaussian graphical models Y Yang, J Etesami, N Kiyavash arXiv preprint arXiv:1509.06449, 2015 | 2 | 2015 |
| RLCG: When reinforcement learning meets coarse graining S Wu, T Liu, Z Wang, W Yan, Y Yang NeurIPS 2022 AI for Science: Progress and Promises, 2022 | 1 | 2022 |
| Fourier learning with cyclical data Y Yang, Z Xiong, T Liu, T Wang, C Wang International Conference on Machine Learning 39, 2022 | 1 | 2022 |
| How Can LLM Guide RL? A Value-Based Approach S Zhang, S Zheng, S Ke, Z Liu, W Jin, J Yuan, Y Yang, H Yang, Z Wang arXiv preprint arXiv:2402.16181, 2024 | | 2024 |
| Machine learning with periodic data Y Yang, T Liu, T Wang, C Wang, Z Xiong US Patent App. US17/666,076, 2023 | | 2023 |
| Efficient learning of temporal dynamics with first-order methods Y Yang University of Illinois at Urbana-Champaign, 2020 | | 2020 |
| An approach to reduce overhead under the VLQ transmission scheme for cooperative spectrum sensing in cognitive radio Y Yang, Q Pan, Y Gao, X Zhang 2011 IEEE Vehicular Technology Conference (VTC Fall), 1-5, 2011 | | 2011 |
Niao HeETH ZürichVerified email at inf.ethz.ch
