- Sample Efficient Stochastic Variance-Reduced Cubic Regularization Method [ArXiv]
Dongruo Zhou, Pan Xu, Quanquan Gu, arXiv:1811.11989, 2018.
- Finding Local Minima via Stochastic Nested Variance Reduction [ArXiv]
Dongruo Zhou, Pan Xu, Quanquan Gu, arXiv:1806.08782, 2018.
- Communication-efficient Distributed Estimation and Inference for Transelliptical Graphical Models [ArXiv]
Pan Xu, Lu Tian, Quanquan Gu, arXiv:1612.09297, 2016.
Conference Proceedings
- Global Convergence of Langevin Dynamics Based Algorithms for Nonconvex Optimization [Link] [ArXiv][Video]
Pan Xu*, Jinghui Chen*, Difan Zou, Quanquan Gu (*: equal contribution)
In Proc. of the 31st Conference on Advances in Neural Information Processing Systems (NeurIPS'2018), Montréal, Canada, 2018. [Spotlight, 3.5%]
- Stochastic Nested Variance Reduction for Nonconvex Optimization [Link] [ArXiv][Video]
Dongrou Zhou, Pan Xu, Quanquan Gu
In Proc. of the 31st Conference on Advances in Neural Information Processing Systems (NeurIPS'2018), Montréal, Canada, 2018. [Spotlight, 3.5%]
- Third-order Smoothness Helps: Even Faster Stochastic Optimization Algorithms for Finding Local Minima [Link] [ArXiv][Video]
Yaodong Yu*, Pan Xu*, Quanquan Gu (*: equal contribution)
In Proc. of the 31st Conference on Advances in Neural Information Processing Systems (NeurIPS'2018), Montréal, Canada, 2018.
- Subsampled Stochastic Variance-Reduced Gradient Langevin Dynamics [Link]
Difan Zou*, Pan Xu*, Quanquan Gu (*: equal contribution)
In Proc. of the 34th International Conference on Uncertainty in Artificial Intelligence (UAI'2018), Monterey, California, 2018.
- Continuous and Discrete-Time Accelerated Stochastic Mirror Descent for Strongly Convex Functions [Link]
Pan Xu*, Tianhao Wang*, Quanquan Gu (*: equal contribution)
In Proc. of the 35th International Conference on Machine Learning (ICML'2018), Stockholm, Sweden, 2018.
- Stochastic Variance-Reduced Cubic Regularized Newton Method [Link][ArXiv]
Dongruo Zhou, Pan Xu, Quanquan Gu
In Proc. of the 35th International Conference on Machine Learning (ICML'2018), Stockholm, Sweden, 2018.
- Stochastic Variance-Reduced Hamilton Monte Carlo Methods [Link][ArXiv]
Difan Zou*, Pan Xu*, Quanquan Gu (*: equal contribution)
In Proc. of the 35th International Conference on Machine Learning (ICML'2018), Stockholm, Sweden, 2018.
- Covariate Adjusted Precision Matrix Estimation via Nonconvex Optimization [Link]
Jinghui Chen, Pan Xu, Lingxiao Wang, Jian Ma, Quanquan Gu
In Proc. of the 35th International Conference on Machine Learning (ICML'2018), Stockholm, Sweden, 2018.
- Accelerated Stochastic Mirror Descent: From Continuous-time Dynamics to Discrete-time Algorithms [Link][PDF]
Pan Xu*, Tianhao Wang*, Quanquan Gu (*: equal contribution)
In Proc. of the 21st International Conference on Artificial Intelligence and Statistics (AISTATS'2018), Playa Blanca, Lanzarote, Canary Islands, 2018.
- Speeding Up Latent Variable Gaussian Graphical Model Estimation via Nonconvex Optimization [Link][ArXiv][Poster][Code]
Pan Xu, Jian Ma, Quanquan Gu
In Proc. of the 30th Conference on Advances in Neural Information Processing Systems (NIPS'2017), Long Beach, CA, USA, 2017.
- Uncertainty Assessment and False Discovery Rate Control in High-Dimensional Granger Causal Inference [Link]
Aditya Chaudhry, Pan Xu, Quanquan Gu
In Proc. of the 34th International Conference on Machine Learning (ICML'2017), Sydney, Australia, 2017.
- Efficient Algorithm for Sparse Tensor-variate Gaussian Graphical Models via Gradient Descent [Link]
Pan Xu, Tingting Zhang, Quanquan Gu
In Proc. of the 20th International Conference on Artificial Intelligence and Statistics (AISTATS'2017), Fort Lauderdale, Florida, USA, 2017.
- Semiparametric Differential Graph Models [Link][Video]
Pan Xu, Quanquan Gu
In Proc. of the 29th Conference on Advances in Neural Information Processing Systems (NIPS'2016), Barcelona, Spain, 2016.
- Forward Backward Greedy Algorithms for Multi-Task Learning with Faster Rates [Link]
Lu Tian, Pan Xu, Quanquan Gu
In Proc. of the 32nd International Conference on Uncertainty in Artificial Intelligence (UAI'2016), New York / New Jersey, USA, 2016.
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