| Efficient private ERM for smooth objectives J Zhang, K Zheng, W Mou, L Wang arXiv preprint arXiv:1703.09947, 2017 | 105 | 2017 |
| Generalization bounds of sgld for non-convex learning: Two theoretical viewpoints W Mou, L Wang, X Zhai, K Zheng Conference on Learning Theory, 605-638, 2018 | 93 | 2018 |
| Differentially private clustering in high-dimensional euclidean spaces MF Balcan, T Dick, Y Liang, W Mou, H Zhang International Conference on Machine Learning, 322-331, 2017 | 57 | 2017 |
| High-Order Langevin Diffusion Yields an Accelerated MCMC Algorithm. W Mou, YA Ma, MJ Wainwright, PL Bartlett, MI Jordan J. Mach. Learn. Res. 22, 42:1-42:41, 2021 | 47 | 2021 |
| Collect at once, use effectively: Making non-interactive locally private learning possible K Zheng, W Mou, L Wang International Conference on Machine Learning, 4130-4139, 2017 | 34 | 2017 |
| Improved bounds for discretization of Langevin diffusions: Near-optimal rates without convexity W Mou, N Flammarion, MJ Wainwright, PL Bartlett Bernoulli 28 (3), 1577-1601, 2022 | 27 | 2022 |
| On linear stochastic approximation: Fine-grained Polyak-Ruppert and non-asymptotic concentration W Mou, CJ Li, MJ Wainwright, PL Bartlett, MI Jordan Conference on Learning Theory, 2947-2997, 2020 | 27 | 2020 |
| Dropout training, data-dependent regularization, and generalization bounds W Mou, Y Zhou, J Gao, L Wang International conference on machine learning, 3645-3653, 2018 | 21 | 2018 |
| An efficient sampling algorithm for non-smooth composite potentials W Mou, N Flammarion, MJ Wainwright, PL Bartlett arXiv preprint arXiv:1910.00551, 2019 | 15 | 2019 |
| Root-sgd: Sharp nonasymptotics and asymptotic efficiency in a single algorithm CJ Li, W Mou, M Wainwright, M Jordan Conference on Learning Theory, 909-981, 2022 | 10 | 2022 |
| A diffusion process perspective on posterior contraction rates for parameters W Mou, N Ho, MJ Wainwright, P Bartlett, MI Jordan arXiv preprint arXiv:1909.00966, 2019 | 10 | 2019 |
| Optimal oracle inequalities for solving projected fixed-point equations W Mou, A Pananjady, MJ Wainwright arXiv preprint arXiv:2012.05299, 2020 | 7 | 2020 |
| On the sample complexity of reinforcement learning with policy space generalization W Mou, Z Wen, X Chen arXiv preprint arXiv:2008.07353, 2020 | 6 | 2020 |
| The impact of local oscillator frequency jitter and laser linewidth to ultra high baud rate coherent systems R Zhang, WJ Jiang, K Kuzmin, Y Weng, W Mou, GK Chang, WI Way Journal of Lightwave Technology 38 (6), 1138-1147, 2019 | 6 | 2019 |
| Optimal and instance-dependent guarantees for Markovian linear stochastic approximation W Mou, A Pananjady, MJ Wainwright, PL Bartlett arXiv preprint arXiv:2112.12770, 2021 | 5 | 2021 |
| Sampling for bayesian mixture models: Mcmc with polynomial-time mixing W Mou, N Ho, MJ Wainwright, PL Bartlett, MI Jordan arXiv preprint arXiv:1912.05153, 2019 | 4 | 2019 |
| Optimal variance-reduced stochastic approximation in Banach spaces W Mou, K Khamaru, MJ Wainwright, PL Bartlett, MI Jordan arXiv preprint arXiv:2201.08518, 2022 | 3 | 2022 |
| Rate redundancy and entropy allocation for PAS-OFDM based mobile fronthaul R Zhang, YW Chen, W Mou, GK Chang Journal of Lightwave Technology 38 (16), 4260-4269, 2020 | 3 | 2020 |
| Entropy Allocation Optimization for PS-OFDM With Constellation Partitioning Based Modeling R Zhang, YW Chen, W Mou, S Yao, GK Chang Journal of Lightwave Technology 38 (21), 6024-6030, 2020 | 2 | 2020 |
| A refined analysis of lsh for well-dispersed data points W Mou, L Wang 2017 Proceedings of the Fourteenth Workshop on Analytic Algorithmics and …, 2017 | 2 | 2017 |
Martin WainwrightProfessor of EECS and Statistics, UC BerkeleyVerified email at berkeley.edu
