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2020 – today
- 2022
[c16]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: 3288-3298- [i16]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 abs/2206.02281 (2022) - 2021
- [j1]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): 804-813 (2021) - [c15]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: 1-4 - [c14]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: 905-913 - [c13]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: 10118-10129 - [c12]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: 12333-12344 - [i15]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 abs/2102.02888 (2021) - [i14]Daochen Zha, Jingru Xie, Wenye Ma, Sheng Zhang, Xiangru Lian, Xia Hu, Ji Liu:
DouZero: Mastering DouDizhu with Self-Play Deep Reinforcement Learning. CoRR abs/2106.06135 (2021) - [i13]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 abs/2107.01499 (2021) - [i12]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 abs/2111.05897 (2021) - 2020
- [i11]Huizhuo Yuan, Xiangru Lian, Ji Liu, Yuren Zhou:
Stochastic Recursive Momentum for Policy Gradient Methods. CoRR abs/2003.04302 (2020) - [i10]Hanlin Tang, Shaoduo Gan, Samyam Rajbhandari, Xiangru Lian, Ji Liu, Yuxiong He, Ce Zhang:
APMSqueeze: A Communication Efficient Adam-Preconditioned Momentum SGD Algorithm. CoRR abs/2008.11343 (2020)
2010 – 2019
- 2019
- [c11]Xiangru Lian, Ji Liu:
Revisit Batch Normalization: New Understanding and Refinement via Composition Optimization. AISTATS 2019: 3254-3263 - [c10]Hanlin Tang, Chen Yu, Xiangru Lian, Tong Zhang, Ji Liu:
DoubleSqueeze: Parallel Stochastic Gradient Descent with Double-pass Error-Compensated Compression. ICML 2019: 6155-6165 - [c9]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: 6926-6935 - [i9]Hanlin Tang, Xiangru Lian, Tong Zhang, Ji Liu:
DoubleSqueeze: Parallel Stochastic Gradient Descent with Double-Pass Error-Compensated Compression. CoRR abs/1905.05957 (2019) - [i8]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 abs/1907.07346 (2019) - [i7]Huizhuo Yuan, Xiangru Lian, Ji Liu:
Stochastic Recursive Variance Reduction for Efficient Smooth Non-Convex Compositional Optimization. CoRR abs/1912.13515 (2019) - 2018
- [c8]Xiangru Lian, Wei Zhang, Ce Zhang, Ji Liu:
Asynchronous Decentralized Parallel Stochastic Gradient Descent. ICML 2018: 3049-3058 - [c7]Hanlin Tang, Xiangru Lian, Ming Yan, Ce Zhang, Ji Liu:
D2: Decentralized Training over Decentralized Data. ICML 2018: 4855-4863 - [i6]Hanlin Tang, Xiangru Lian, Ming Yan, Ce Zhang, Ji Liu:
D2: Decentralized Training over Decentralized Data. CoRR abs/1803.07068 (2018) - [i5]Xiangru Lian, Ji Liu:
Revisit Batch Normalization: New Understanding from an Optimization View and a Refinement via Composition Optimization. CoRR abs/1810.06177 (2018) - 2017
- [c6]Xiangru Lian, Mengdi Wang, Ji Liu:
Finite-sum Composition Optimization via Variance Reduced Gradient Descent. AISTATS 2017: 1159-1167 - [c5]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: 5330-5340 - [i4]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 abs/1705.09056 (2017) - [i3]Xiangru Lian, Wei Zhang, Ce Zhang, Ji Liu:
Asynchronous Decentralized Parallel Stochastic Gradient Descent. CoRR abs/1710.06952 (2017) - 2016
- [c4]Wei Zhang, Suyog Gupta, Xiangru Lian, Ji Liu:
Staleness-Aware Async-SGD for Distributed Deep Learning. IJCAI 2016: 2350-2356 - [c3]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: 3054-3062 - [c2]Yang You, Xiangru Lian, Ji Liu, Hsiang-Fu Yu, Inderjit S. Dhillon, James Demmel, Cho-Jui Hsieh:
Asynchronous Parallel Greedy Coordinate Descent. NIPS 2016: 4682-4690 - 2015
- [c1]Xiangru Lian, Yijun Huang, Yuncheng Li, Ji Liu:
Asynchronous Parallel Stochastic Gradient for Nonconvex Optimization. NIPS 2015: 2737-2745 - [i2]Xiangru Lian, Yijun Huang, Yuncheng Li, Ji Liu:
Asynchronous Parallel Stochastic Gradient for Nonconvex Optimization. CoRR abs/1506.08272 (2015) - [i1]Wei Zhang, Suyog Gupta, Xiangru Lian, Ji Liu:
Staleness-aware Async-SGD for Distributed Deep Learning. CoRR abs/1511.05950 (2015)
Coauthor Index
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