I’m currently a 3rd-year Ph.D. student at UCLA CS, advised by Prof. Cho-Jui Hsieh. My research interest lies in automated, robust, and efficient machine learning. Before coming to UCLA, I received my B.Eng. degree from the Department of Electronic Engineering, Tsinghua University. During my undergrad, I worked closely with Prof. Yong Li and Prof. Quanming Yao on the topic of recommender system. I also spent a wonderful summer at MIT EECS advised by Prof. Song Han, working on AutoML.
[07/2021] One paper on “architecture performance predictor” got accepted to ICCV'21.
[06/2021] I joined Google Brain, AutoML Team as a summer intern.
[02/2021] Our paper on “robust and accurate object detection” got accepted to CVPR'21.
[01/2021] Two papers (1 oral) got accepted to ICLR'21.
[07/2020] I started my internship at Google Research, Mobile Vision Team, hosted by Dr. Boqing Gong and Dr. Li Zhang.
[05/2020] Our paper on “stabilizing neural architecture search” got accepted to ICML'20.
[01/2020] Our paper on “searching for neural interaction function” was accepted to WWW'20.
[09/2019] I started my Ph.D. journey at UCLA CS.
[07/2019] I received B.Eng. from Tsinghua University as an outstanding graduate.
*indicates equal contribution
When Vision Transformers Outperform ResNets without Pre-training or Strong Data Augmentations
Xiangning Chen, Cho-Jui Hsieh, Boqing Gong
[JAX Checkpoint] [PyTorch Checkpoint]
Concurrent Adversarial Learning for Large-Batch Training
Yong Liu, Xiangning Chen, Minhao Cheng, Cho-Jui Hsieh, Yang You
2.5D Visual Relationship Detection
Yu-Chuan Su, Soravit Changpinyo, Xiangning Chen, Sathish Thoppay, Cho-Jui Hsieh, Lior Shapira, Radu Soricut, Hartwig Adam, Matthew Brown, Ming-Hsuan Yang, Boqing Gong
RANK-NOSH: Efficient Predictor-Based Architecture Search via Non-Uniform Successive Halving
Ruochen Wang, Xiangning Chen, Minhao Cheng, Xiaocheng Tang, Cho-Jui Hsieh
Robust and Accurate Object Detection via Adversarial Learning
Xiangning Chen, Cihang Xie, Mingxing Tan, Li Zhang, Cho-Jui Hsieh, Boqing Gong
CVPR 2021 [TensorFlow Checkpoint] [Colab]
Rethinking Architecture Selection in Differentiable NAS
Ruochen Wang, Minhao Cheng, Xiangning Chen, Xiaocheng Tang, Cho-Jui Hsieh
ICLR 2021 (oral, outstanding paper award) [Code]
Stabilizing Differentiable Architecture Search via Perturbation-based Regularization
Xiangning Chen, Cho-Jui Hsieh
ICML 2020 [Code] [Video] [Media]
Efficient Neural Interaction Function Search for Collaborative Filtering
Quanming Yao *, Xiangning Chen *, James Kwok, Yong Li, Cho-Jui Hsieh
WWW 2020 [Code]
Neural Feature Search: A Neural Architecture for Automated Feature Engineering
Xiangning Chen, Qingwei Lin, Chuan Luo, Xudong Li, Hongyu Zhang, Yong Xu, Yingnong Dang, Kaixin Sui, Xu Zhang, Bo Qiao, Weiyi Zhang, Wei Wu, Murali Chintalapati, Dongmei Zhang
ICDM 2019 [Microsoft Research Page]
DeepAPF: Deep Attentive Probabilistic Factorization for Multi-site Video Recommendation
Huan Yan, Xiangning Chen, Chen Gao, Yong Li, Depeng Jin
Cross-domain Recommendation Without Sharing User-relevant Data
Chen Gao, Xiangning Chen, Fuli Feng, Kai Zhao, Xiangnan He, Yong Li, Depeng Jin
Neural Multi-task Recommendation from Multi-behavior Data
Chen Gao, Xiangnan He, Dahua Gan, Xiangning Chen, Fuli Feng, Yong Li, Tat-Seng Chua, Depeng Jin
ICLR Outstanding Paper Award, 2021
Outstanding Graduate & Bachelor Thesis, Tsinghua University, 2019
2nd place (feedback phase), NeurIPS AutoML Challenge, 2018
Qualcomm Scholarship, 2018
Guangzhou Pharmaceutical Corporation Scholarship, 2017
Geru Zheng Scholarship, 2016
2019.9 - present, University of California, Los Angeles
Ph.D. student in Computer Science
2016.8 - 2019.7, Tsinghua University
B.Ec. in Economics (Second Degree)
2015.8 - 2019.7, Tsinghua University
B.Eng. in Electronic Engineering
UCLA CS 180: Algorithms & Complexity, Teaching Assistant, 2021 Spring
Address: UCLA Engineering VI, 404 Westwood Plaza, Los Angeles, CA 90095
Email: xiangning at cs dot ucla dot edu