2 citations · 2 across the 2 of their papers we have counts for
3 papers
cs.LG2021
Mitigating Performance Saturation in Neural Marked Point Processes: Architectures and Loss Functions
Tianbo Li, Tianze Luo, Yiping Ke +1
Attributed event sequences are commonly encountered in practice. A recent research line focuses on incorporating neural networks with the statistical model -- marked point processe…
cs.LG2020★ 2 cited
Subdomain Adaptation with Manifolds Discrepancy Alignment
Pengfei Wei, Yiping Ke, Xinghua Qu +1
Reducing domain divergence is a key step in transfer learning problems. Existing works focus on the minimization of global domain divergence. However, two domains may consist of se…
cs.LG2016
Stochastic Variance Reduced Riemannian Eigensolver
Zhiqiang Xu, Yiping Ke
We study the stochastic Riemannian gradient algorithm for matrix eigen-decomposition. The state-of-the-art stochastic Riemannian algorithm requires the learning rate to decay to ze…