Neural Network/Deep Learning
Xialiang Dou, Tengyuan Liang. Training Neural Networks as Learning Data-adaptive Kernels: Provable Representation and Approximation Benefits. arXiv:1901.07114, 2019.
Tengyuan Liang, James Stokes. Interaction Matters: A Note on Non-asymptotic Local Convergence of Generative Adversarial Networks. AISTATS, accepted, 2018.
Tengyuan Liang, Tomaso Poggio, Alexander Rakhlin, James Stokes. Fisher-Rao Metric, Geometry, and Complexity of Neural Networks. AISTATS, accepted, 2018.
Tengyuan Liang. On How Well Generative Adversarial Networks Learn Densities: Nonparametric and Parametric Results. arXiv:1811.03179, 2018.
Max Farrell, Tengyuan Liang, Sanjog Misra. Deep Neural Networks for Estimation and Inference: Application to Causal Effects and Other Semiparametric Estimands. arXiv:1809.09953, 2018.