no code implementations • 28 Dec 2022 • Rohan Sinha, Apoorva Sharma, Somrita Banerjee, Thomas Lew, Rachel Luo, Spencer M. Richards, Yixiao Sun, Edward Schmerling, Marco Pavone
When testing conditions differ from those represented in training data, so-called out-of-distribution (OOD) inputs can mar the reliability of learned components in the modern robot autonomy stack.
no code implementations • 17 Nov 2022 • Rachel Luo, Rohan Sinha, Yixiao Sun, Ali Hindy, Shengjia Zhao, Silvio Savarese, Edward Schmerling, Marco Pavone
When deploying modern machine learning-enabled robotic systems in high-stakes applications, detecting distribution shift is critical.
no code implementations • 7 Jan 2022 • Julian Martinez-Iriarte, Gabriel Montes-Rojas, Yixiao Sun
The location-scale shift is intended to study a counterfactual policy aimed at changing not only the mean or location of a covariate but also its dispersion or scale.
no code implementations • 29 Oct 2020 • Julian Martinez-Iriarte, Yixiao Sun
This paper studies the identification and estimation of policy effects when treatment status is binary and endogenous.
15 code implementations • 22 Nov 2017 • Xuan Zhang, Hao Luo, Xing Fan, Weilai Xiang, Yixiao Sun, Qiqi Xiao, Wei Jiang, Chi Zhang, Jian Sun
In this paper, we propose a novel method called AlignedReID that extracts a global feature which is jointly learned with local features.
Ranked #1 on Person Re-Identification on CUHK-SYSU