no code implementations • 26 Mar 2024 • JoonHwan Cho, Yao Luo, Ruli Xiao
Economic data are often contaminated by measurement errors and truncated by ranking.
no code implementations • 27 Mar 2023 • Daniel Ackerberg, Garth Frazer, Kyoo il Kim, Yao Luo, Yingjun Su
We then show that the problem can persist in a broader set of models but disappears in models under stronger timing assumptions.
no code implementations • 7 Oct 2022 • Yao Luo, Peijun Sang, Ruli Xiao
We establish nonparametric identification of auction models with continuous and nonseparable unobserved heterogeneity using three consecutive order statistics of bids.
no code implementations • 25 May 2022 • Yao Luo, Ruli Xiao
Auction data often contain information on only the most competitive bids as opposed to all bids.
no code implementations • 28 Apr 2022 • Yao Luo, Peijun Sang
Estimating structural models is an essential tool for economists.
no code implementations • 15 Aug 2019 • Emmanuel Guerre, Yao Luo
Our benchmark model assumes an exogenous number of bidders N. We show that, if the bidders observe N, the resulting discontinuities in the winning bid density can be used to identify the distribution of N. The private value distribution can be nonparametrically identified in a second step.
no code implementations • 16 May 2019 • Yao Luo, Xiaoguang Tu, Mei Xie
3D face reconstruction from a single 2D image is a very important topic in computer vision.
2 code implementations • 22 Mar 2019 • Xiaoguang Tu, Jian Zhao, Zi-Hang Jiang, Yao Luo, Mei Xie, Yang Zhao, Linxiao He, Zheng Ma, Jiashi Feng
3D face reconstruction from a single 2D image is a challenging problem with broad applications.
Ranked #7 on Face Alignment on AFLW2000-3D
no code implementations • 17 Jan 2019 • Xiaoguang Tu, Hengsheng Zhang, Mei Xie, Yao Luo, Yuefei Zhang, Zheng Ma
We propose a CNN framework using sparsely labeled data from the target domain to learn features that are invariant across domains for face anti-spoofing.
no code implementations • 17 Jan 2019 • Xiaoguang Tu, Hengsheng Zhang, Mei Xie, Yao Luo, Yuefei Zhang, Zheng Ma
Spatio-temporal information is very important to capture the discriminative cues between genuine and fake faces from video sequences.