Learning Two-layer Neural Networks with Symmetric Inputs,借助对称输入学习双层神经网络. ICLR 2019. https://arxiv.org/abs/1810.06793
Understanding Composition of Word Embeddings via Tensor Decomposition,通过张量分解理解词嵌入的成分. ICLR 2019. https://openreview.net/forum?id=H1eqjiCctX
Stronger generalization bounds for deep nets via a compression approach,通过压缩方式为深度神经网络赋予更强的泛化边界. ICML 2018. https://arxiv.org/abs/1802.05296
Minimizing Nonconvex Population Risk from Rough Empirical Risk,从粗糙的经验风险中最小化非凸种群风险. NeurIPS 2018. https://arxiv.org/abs/1803.09357
Beyond Log-concavity: Provable Guarantees for Sampling Multi-modal Distributions using Simulated Tempering Langevin Monte Carlo,超越对数凹面:通过仿真时序郎之万蒙特卡洛实现采样多模态分布的可证明保证. NIPS 2017 Bayesian Inference Workshop. NeurIPS 2018. https://arxiv.org/abs/1812.00793
Global Convergence of Policy Gradient Methods for Linearized Control Problems,用于线性化控制问题的策略梯度方法的全局收敛性. ICML 2018. https://arxiv.org/abs/1801.05039
Learning One-hidden-layer Neural Networks with Landscape Design,通过曲面设计学习单层隐层的神经网络. ICLR 2018. https://arxiv.org/abs/1711.00501
Generalization and Equilibrium in Generative Adversarial Nets (GANs),对抗性生成式网络的泛化性和均衡研究. ICML 2017. https://arxiv.org/abs/1703.00573
No Spurious Local Minima in Nonconvex Low Rank Problems: A Unified Geometric Analysis,低阶非凸问题中不存在虚假的局部极小值:一个统一的几何分析. ICML 2017. https://arxiv.org/abs/1704.00708
How to Escape Saddle Points Efficiently,如何高效地离开驻点. ICML 2017. https://arxiv.org/abs/1703.00887
On the Optimization Landscape of Tensor decompositions,关于张量分解的优化图像.NIPS 2016 非凸 workshop 最佳理论研究奖. https://sites.google.com/site/nonconvexnips2016/files/Paper8.pdf
Matrix Completion has No Spurious Local Minimum,矩阵期满中不存在虚假的局部极小值. NIPS 2016 最佳学生论文奖. http://arxiv.org/abs/1605.07272
Provable Algorithms for Inference in Topic Models,话题模型中可证明的推理算法. In ICML 2016. http://arxiv.org/abs/1605.08491
Efficient Algorithms for Large-scale Generalized Eigenvector Computation and Canonical Correlation Analysis,几个高效的大规模泛化特征向量计算和规范关联分析算法. ICML 2016. http://arxiv.org/abs/1604.03930
Rich Component Analysis,富成分分析. In ICML 2016. http://arxiv.org/abs/1507.03867
Intersecting Faces: Non-negative Matrix Factorization With New Guarantees,相交的截面:带有新的保证的非负矩阵乘法. ICML 2015. http://arxiv.org/abs/1507.02189
Un-regularizing: approximate proximal point and faster stochastic algorithms for empirical risk minimization,反规范化:用于经验风险最小化的逼近近似点和更快的随机算法. ICML 2015. http://arxiv.org/abs/1506.07512
此外他还有多篇论文发表在各年的 COLT(Annual Conference on Learning Theory,ACM 主办,计算学习理论顶级会议) 中。