Xiangru Lian

Publication Activity (10 Years)

Years Active: 2015-2022
Publications (10 Years): 30

Top Topics

Policy Gradient Methods

Unmanned Aerial Vehicles

Top Venues

Publications

Zhenyu Hu, Zhenyu Wu, Pengcheng Pi, Yunhe Xue, Jiayi Shen, Jianchao Tan, Xiangru Lian, Zhangyang Wang, Ji Liu
E^2VTS: Energy-Efficient Video Text Spotting from Unmanned Aerial Vehicles. CoRR (2022)
Xiangru Lian, Binhang Yuan, Xuefeng Zhu, Yulong Wang, Yongjun He, Honghuan Wu, Lei Sun, Haodong Lyu, Chengjun Liu, Xing Dong, Yiqiao Liao, Mingnan Luo, Congfei Zhang, Jingru Xie, Haonan Li, Lei Chen, Renjie Huang, Jianying Lin, Chengchun Shu, Xuezhong Qiu, Zhishan Liu, Dongying Kong, Lei Yuan, Hai Yu, Sen Yang, Ce Zhang, Ji Liu
Persia: An Open, Hybrid System Scaling Deep Learning-based Recommenders up to 100 Trillion Parameters. KDD (2022)
Daochen Zha, Jingru Xie, Wenye Ma, Sheng Zhang, Xiangru Lian, Xia Hu, Ji Liu
DouZero: Mastering DouDizhu with Self-Play Deep Reinforcement Learning. ICML (2021)
Daochen Zha, Jingru Xie, Wenye Ma, Sheng Zhang, Xiangru Lian, Xia Hu, Ji Liu
DouZero: Mastering DouDizhu with Self-Play Deep Reinforcement Learning. CoRR (2021)
Zhenyu Hu, Pengcheng Pi, Zhenyu Wu, Yunhe Xue, Jiayi Shen, Jianchao Tan, Xiangru Lian, Zhangyang Wang, Ji Liu
E2VTS: Energy-Efficient Video Text Spotting From Unmanned Aerial Vehicles. CVPR Workshops (2021)
Shaoduo Gan, Xiangru Lian, Rui Wang, Jianbin Chang, Chengjun Liu, Hongmei Shi, Shengzhuo Zhang, Xianghong Li, Tengxu Sun, Jiawei Jiang, Binhang Yuan, Sen Yang, Ji Liu, Ce Zhang
BAGUA: Scaling up Distributed Learning with System Relaxations. Proc. VLDB Endow. 15 (4) (2021)
Hanlin Tang, Shaoduo Gan, Ammar Ahmad Awan, Samyam Rajbhandari, Conglong Li, Xiangru Lian, Ji Liu, Ce Zhang, Yuxiong He
1-bit Adam: Communication Efficient Large-Scale Training with Adam's Convergence Speed. ICML (2021)
Shaoduo Gan, Xiangru Lian, Rui Wang, Jianbin Chang, Chengjun Liu, Hongmei Shi, Shengzhuo Zhang, Xianghong Li, Tengxu Sun, Jiawei Jiang, Binhang Yuan, Sen Yang, Ji Liu, Ce Zhang
BAGUA: Scaling up Distributed Learning with System Relaxations. CoRR (2021)
Hanlin Tang, Shaoduo Gan, Ammar Ahmad Awan, Samyam Rajbhandari, Conglong Li, Xiangru Lian, Ji Liu, Ce Zhang, Yuxiong He
1-bit Adam: Communication Efficient Large-Scale Training with Adam's Convergence Speed. CoRR (2021)
Xiangru Lian, Binhang Yuan, Xuefeng Zhu, Yulong Wang, Yongjun He, Honghuan Wu, Lei Sun, Haodong Lyu, Chengjun Liu, Xing Dong, Yiqiao Liao, Mingnan Luo, Congfei Zhang, Jingru Xie, Haonan Li, Lei Chen, Renjie Huang, Jianying Lin, Chengchun Shu, Xuezhong Qiu, Zhishan Liu, Dongying Kong, Lei Yuan, Hai Yu, Sen Yang, Ce Zhang, Ji Liu
Persia: An Open, Hybrid System Scaling Deep Learning-based Recommenders up to 100 Trillion Parameters. CoRR (2021)
Xiao Hu, Ming-Ching Chang, Yuwei Chen, Rahul Sridhar, Zhenyu Hu, Yunhe Xue, Zhenyu Wu, Pengcheng Pi, Jiayi Shen, Jianchao Tan, Xiangru Lian, Ji Liu, Zhangyang Wang, Chia-Hsiang Liu, Yu-Shin Han, Yuan-Yao Sung, Yi Lee, Kai-Chiang Wu, Wei-Xiang Guo, Rick Lee, Shengwen Liang, Zerun Wang, Guiguang Ding, Gang Zhang, Teng Xi, Yubei Chen, Han Cai, Ligeng Zhu, Zhekai Zhang, Song Han, Seonghwan Jeong, YoungMin Kwon, Tianzhe Wang, Jeffery Pan
The 2020 Low-Power Computer Vision Challenge. AICAS (2021)
Hanlin Tang, Shaoduo Gan, Samyam Rajbhandari, Xiangru Lian, Ji Liu, Yuxiong He, Ce Zhang
APMSqueeze: A Communication Efficient Adam-Preconditioned Momentum SGD Algorithm. CoRR (2020)
Huizhuo Yuan, Xiangru Lian, Ji Liu, Yuren Zhou
Stochastic Recursive Momentum for Policy Gradient Methods. CoRR (2020)
Xiangru Lian, Ji Liu
Revisit Batch Normalization: New Understanding and Refinement via Composition Optimization. AISTATS (2019)
Hanlin Tang, Xiangru Lian, Tong Zhang, Ji Liu
DoubleSqueeze: Parallel Stochastic Gradient Descent with Double-Pass Error-Compensated Compression. CoRR (2019)
Huizhuo Yuan, Xiangru Lian, Ji Liu
Stochastic Recursive Variance Reduction for Efficient Smooth Non-Convex Compositional Optimization. CoRR (2019)
Huizhuo Yuan, Xiangru Lian, Chris Junchi Li, Ji Liu, Wenqing Hu
Efficient Smooth Non-Convex Stochastic Compositional Optimization via Stochastic Recursive Gradient Descent. NeurIPS (2019)
Hanlin Tang, Chen Yu, Xiangru Lian, Tong Zhang, Ji Liu
DoubleSqueeze: Parallel Stochastic Gradient Descent with Double-pass Error-Compensated Compression. ICML (2019)
Hanlin Tang, Xiangru Lian, Shuang Qiu, Lei Yuan, Ce Zhang, Tong Zhang, Ji Liu
DeepSqueeze: Parallel Stochastic Gradient Descent with Double-Pass Error-Compensated Compression. CoRR (2019)
Hanlin Tang, Xiangru Lian, Ming Yan, Ce Zhang, Ji Liu
: Decentralized Training over Decentralized Data. CoRR (2018)
Hanlin Tang, Xiangru Lian, Ming Yan, Ce Zhang, Ji Liu
: Decentralized Training over Decentralized Data. ICML (2018)
Xiangru Lian, Ji Liu
Revisit Batch Normalization: New Understanding from an Optimization View and a Refinement via Composition Optimization. CoRR (2018)
Xiangru Lian, Wei Zhang, Ce Zhang, Ji Liu
Asynchronous Decentralized Parallel Stochastic Gradient Descent. ICML (2018)
Xiangru Lian, Wei Zhang, Ce Zhang, Ji Liu
Asynchronous Decentralized Parallel Stochastic Gradient Descent. CoRR (2017)
Xiangru Lian, Ce Zhang, Huan Zhang, Cho-Jui Hsieh, Wei Zhang, Ji Liu
Can Decentralized Algorithms Outperform Centralized Algorithms? A Case Study for Decentralized Parallel Stochastic Gradient Descent. CoRR (2017)
Xiangru Lian, Mengdi Wang, Ji Liu
Finite-sum Composition Optimization via Variance Reduced Gradient Descent. AISTATS (2017)
Xiangru Lian, Ce Zhang, Huan Zhang, Cho-Jui Hsieh, Wei Zhang, Ji Liu
Can Decentralized Algorithms Outperform Centralized Algorithms? A Case Study for Decentralized Parallel Stochastic Gradient Descent. NIPS (2017)
Xiangru Lian, Huan Zhang, Cho-Jui Hsieh, Yijun Huang, Ji Liu
A Comprehensive Linear Speedup Analysis for Asynchronous Stochastic Parallel Optimization from Zeroth-Order to First-Order. NIPS (2016)
Yang You, Xiangru Lian, Ji Liu, Hsiang-Fu Yu, Inderjit S. Dhillon, James Demmel, Cho-Jui Hsieh
Asynchronous Parallel Greedy Coordinate Descent. NIPS (2016)
Wei Zhang, Suyog Gupta, Xiangru Lian, Ji Liu
Staleness-Aware Async-SGD for Distributed Deep Learning. IJCAI (2016)
Xiangru Lian, Yijun Huang, Yuncheng Li, Ji Liu
Asynchronous Parallel Stochastic Gradient for Nonconvex Optimization. CoRR (2015)
Wei Zhang, Suyog Gupta, Xiangru Lian, Ji Liu
Staleness-aware Async-SGD for Distributed Deep Learning. CoRR (2015)
Xiangru Lian, Yijun Huang, Yuncheng Li, Ji Liu
Asynchronous Parallel Stochastic Gradient for Nonconvex Optimization. NIPS (2015)