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ORCIDJi Liu 0002
刘霁
Person information
- unicode name: 刘霁
- affiliation: Kwai Inc., Seattle AI Lab, WA, USA
- affiliation: Kuaishou Technology, Beijing, China
- affiliation (former): University of Rochester, Department of Computer Science, NY, USA
- affiliation (former): Tencent AI Lab, China
- affiliation (former, PhD): University of Wisconsin-Madison, Department of Computer Sciences, WI, USA
- affiliation (former): Arizona State University, Department of Computer Science and Engineering, Tempe, AZ, USA
Other persons with the same name
- Ji Liu — disambiguation page
- Ji Liu 0001
![[0000-0003-2871-9888]](https://dblp.dagstuhl.de/img/orcid-mark.12x12.png "0000-0003-2871-9888")
— Stony Brook University, NY, USA (and 2 more) - Ji Liu 0003 — Baidu Inc., Baidu Research, Beijing, China (and 2 more)
- Ji Liu 0004 — Pennsylvania State University, Department of Mechanical and Nuclear Engineering, University Park, PA, USA
- Ji Liu 0005 — University of Science and Technology Beijing, School of Computer and Communication Engineering, China (and 1 more)
- Ji Liu 0006 — Chongqing University, College of Computer Science, China
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2020 – today
- 2022
[j32]Shupeng Gui, Xiangliang Zhang, Pan Zhong, Shuang Qiu, Mingrui Wu, Jieping Ye, Zhengdao Wang, Ji Liu:
PINE: Universal Deep Embedding for Graph Nodes via Partial Permutation Invariant Set Functions. IEEE Trans. Pattern Anal. Mach. Intell. 44(2): 770-782 (2022)- [i49]Shixing Yu, Tianlong Chen, Jiayi Shen, Huan Yuan, Jianchao Tan, Sen Yang, Ji Liu, Zhangyang Wang:
Unified Visual Transformer Compression. CoRR abs/2203.08243 (2022) - 2021
- [j31]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) - [c59]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 - [c58]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 - [c57]Xiaohan Ding, Tianxiang Hao, Jianchao Tan, Ji Liu, Jungong Han, Yuchen Guo, Guiguang Ding:
ResRep: Lossless CNN Pruning via Decoupling Remembering and Forgetting. ICCV 2021: 4490-4500 - [c56]Yi Guo, Huan Yuan, Jianchao Tan, Zhangyang Wang, Sen Yang, Ji Liu:
GDP: Stabilized Neural Network Pruning via Gates with Differentiable Polarization. ICCV 2021: 5219-5230 - [c55]Xiong Zhang, Hongsheng Huang, Jianchao Tan, Hongmin Xu, Cheng Yang, Guozhu Peng, Lei Wang, Ji Liu:
Hand Image Understanding via Deep Multi-Task Learning. ICCV 2021: 11261-11272 - [c54]Jiayi Shen, Haotao Wang, Shupeng Gui, Jianchao Tan, Zhangyang Wang, Ji Liu:
UMEC: Unified model and embedding compression for efficient recommendation systems. ICLR 2021 - [c53]Xuefan Zha, Wentao Zhu, Xun Lv, Sen Yang, Ji Liu:
Shifted Chunk Transformer for Spatio-Temporal Representational Learning. NeurIPS 2021: 11384-11396 - [c52]Shun Lu, Jixiang Li, Jianchao Tan, Sen Yang, Ji Liu:
TNASP: A Transformer-based NAS Predictor with a Self-evolution Framework. NeurIPS 2021: 15125-15137 - [c51]Hanlin Tang, Yao Li, Ji Liu, Ming Yan:
ErrorCompensatedX: error compensation for variance reduced algorithms. NeurIPS 2021: 18102-18113 - [i48]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) - [i47]Xiong Zhang, Hongsheng Huang, Jianchao Tan, Hongmin Xu, Cheng Yang, Guozhu Peng, Lei Wang, Ji Liu:
Hand Image Understanding via Deep Multi-Task Learning. CoRR abs/2107.11646 (2021) - [i46]Shangfeng Dai, Haobin Lin, Zhichen Zhao, Jianying Lin, Honghuan Wu, Zhe Wang, Sen Yang, Ji Liu:
POSO: Personalized Cold Start Modules for Large-scale Recommender Systems. CoRR abs/2108.04690 (2021) - [i45]Weicong Ding, Hanlin Tang, Jingshuo Feng, Lei Yuan, Sen Yang, Guangxu Yang, Jie Zheng, Jing Wang, Qiang Su, Dong Zheng, Xuezhong Qiu, Yongqi Liu, Yuxuan Chen, Yang Liu, Chao Song, Dongying Kong, Kai Ren, Peng Jiang, Qiao Lian, Ji Liu:
PASTO: Strategic Parameter Optimization in Recommendation Systems - Probabilistic is Better than Deterministic. CoRR abs/2108.09076 (2021) - [i44]Yi Guo, Huan Yuan, Jianchao Tan, Zhangyang Wang, Sen Yang, Ji Liu:
GDP: Stabilized Neural Network Pruning via Gates with Differentiable Polarization. CoRR abs/2109.02220 (2021) - [i43]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
- [j30]Ji Liu, Ce Zhang:
Distributed Learning Systems with First-Order Methods. Found. Trends Databases 9(1): 1-100 (2020) - [j29]Hongyu Xu, Zhangyang Wang, Haichuan Yang, Ding Liu, Ji Liu:
Learning Simple Thresholded Features With Sparse Support Recovery. IEEE Trans. Circuits Syst. Video Technol. 30(4): 983-997 (2020) - [j28]Xingxing Zhang, Shupeng Gui, Zhenfeng Zhu, Yao Zhao, Ji Liu:
Hierarchical Prototype Learning for Zero-Shot Recognition. IEEE Trans. Multim. 22(7): 1692-1703 (2020) - [c50]Haichuan Yang, Shupeng Gui, Yuhao Zhu, Ji Liu:
Automatic Neural Network Compression by Sparsity-Quantization Joint Learning: A Constrained Optimization-Based Approach. CVPR 2020: 2175-2185 - [c49]Hui Chen, Guiguang Ding, Xudong Liu, Zijia Lin, Ji Liu, Jungong Han:
IMRAM: Iterative Matching With Recurrent Attention Memory for Cross-Modal Image-Text Retrieval. CVPR 2020: 12652-12660 - [c48]Lin Huang, Jianchao Tan, Ji Liu, Junsong Yuan:
Hand-Transformer: Non-Autoregressive Structured Modeling for 3D Hand Pose Estimation. ECCV (25) 2020: 17-33 - [c47]Haotao Wang, Shupeng Gui, Haichuan Yang, Ji Liu, Zhangyang Wang:
GAN Slimming: All-in-One GAN Compression by a Unified Optimization Framework. ECCV (4) 2020: 54-73 - [c46]Lin Huang, Jianchao Tan, Jingjing Meng, Ji Liu, Junsong Yuan:
HOT-Net: Non-Autoregressive Transformer for 3D Hand-Object Pose Estimation. ACM Multimedia 2020: 3136-3145 - [c45]Haotao Wang, Tianlong Chen, Shupeng Gui, Ting-Kuei Hu, Ji Liu, Zhangyang Wang:
Once-for-All Adversarial Training: In-Situ Tradeoff between Robustness and Accuracy for Free. NeurIPS 2020 - [i42]Hui Chen, Guiguang Ding, Xudong Liu, Zijia Lin, Ji Liu, Jungong Han:
IMRAM: Iterative Matching with Recurrent Attention Memory for Cross-Modal Image-Text Retrieval. CoRR abs/2003.03772 (2020) - [i41]Bo Liu, Ian Gemp, Mohammad Ghavamzadeh, Ji Liu, Sridhar Mahadevan, Marek Petrik:
Proximal Gradient Temporal Difference Learning: Stable Reinforcement Learning with Polynomial Sample Complexity. CoRR abs/2006.03976 (2020) - [i40]Bo Liu, Sridhar Mahadevan, Ji Liu:
Regularized Off-Policy TD-Learning. CoRR abs/2006.05314 (2020) - [i39]Xiaohan Ding, Tianxiang Hao, Ji Liu, Jungong Han, Yuchen Guo, Guiguang Ding:
Lossless CNN Channel Pruning via Gradient Resetting and Convolutional Re-parameterization. CoRR abs/2007.03260 (2020) - [i38]Haotao Wang, Shupeng Gui, Haichuan Yang, Ji Liu, Zhangyang Wang:
GAN Slimming: All-in-One GAN Compression by A Unified Optimization Framework. CoRR abs/2008.11062 (2020) - [i37]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) - [i36]Runze Su, Fei Tao, Xudong Liu, Haoran Wei, Xiaorong Mei, Zhiyao Duan, Lei Yuan, Ji Liu, Yuying Xie:
Themes Inferred Audio-visual Correspondence Learning. CoRR abs/2009.06573 (2020) - [i35]Haotao Wang, Tianlong Chen, Shupeng Gui, Ting-Kuei Hu, Ji Liu, Zhangyang Wang:
Once-for-All Adversarial Training: In-Situ Tradeoff between Robustness and Accuracy for Free. CoRR abs/2010.11828 (2020)
2010 – 2019
- 2019
- [j27]Dongdong Hou, Yang Cong, Gan Sun, Ji Liu, Xiaowei Xu:
Anomaly detection via adaptive greedy model. Neurocomputing 330: 369-379 (2019) - [j26]Gan Sun, Yang Cong, Ji Liu, Lianqing Liu, Xiaowei Xu, Haibin Yu:
Lifelong Metric Learning. IEEE Trans. Cybern. 49(8): 3168-3179 (2019) - [j25]Liu Liu, Ji Liu, Dacheng Tao:
Dualityfree Methods for Stochastic Composition Optimization. IEEE Trans. Neural Networks Learn. Syst. 30(4): 1205-1217 (2019) - [j24]Xingxing Zhang, Zhenfeng Zhu, Yao Zhao, Dongxia Chang, Ji Liu:
Seeing All From a Few: ℓ1-Norm-Induced Discriminative Prototype Selection. IEEE Trans. Neural Networks Learn. Syst. 30(7): 1954-1966 (2019) - [j23]Ke Ren, Haichuan Yang, Yu Zhao, Wu Chen, Mingshan Xue, Hongyu Miao, Shuai Huang, Ji Liu:
A Robust AUC Maximization Framework With Simultaneous Outlier Detection and Feature Selection for Positive-Unlabeled Classification. IEEE Trans. Neural Networks Learn. Syst. 30(10): 3072-3083 (2019) - [c44]Xiangru Lian, Ji Liu:
Revisit Batch Normalization: New Understanding and Refinement via Composition Optimization. AISTATS 2019: 3254-3263 - [c43]Aditya R. Bhattacharya, Ji Liu, Shayok Chakraborty:
A Generic Active Learning Framework for Class Imbalance Applications. BMVC 2019: 121 - [c42]Haichuan Yang, Yuhao Zhu, Ji Liu:
ECC: Platform-Independent Energy-Constrained Deep Neural Network Compression via a Bilinear Regression Model. CVPR 2019: 11206-11215 - [c41]Carson Eisenach, Haichuan Yang, Ji Liu, Han Liu:
Marginal Policy Gradients: A Unified Family of Estimators for Bounded Action Spaces with Applications. ICLR (Poster) 2019 - [c40]Haichuan Yang, Yuhao Zhu, Ji Liu:
Energy-Constrained Compression for Deep Neural Networks via Weighted Sparse Projection and Layer Input Masking. ICLR (Poster) 2019 - [c39]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 - [c38]Chen Yu, Hanlin Tang, Cédric Renggli, Simon Kassing, Ankit Singla, Dan Alistarh, Ce Zhang, Ji Liu:
Distributed Learning over Unreliable Networks. ICML 2019: 7202-7212 - [c37]Shupeng Gui, Haotao Wang, Haichuan Yang, Chen Yu, Zhangyang Wang, Ji Liu:
Model Compression with Adversarial Robustness: A Unified Optimization Framework. NeurIPS 2019: 1283-1294 - [c36]Xiaohan Ding, Guiguang Ding, Xiangxin Zhou, Yuchen Guo, Jungong Han, Ji Liu:
Global Sparse Momentum SGD for Pruning Very Deep Neural Networks. NeurIPS 2019: 6379-6391 - [c35]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 - [i34]Shupeng Gui, Haotao Wang, Chen Yu, Haichuan Yang, Zhangyang Wang, Ji Liu:
Adversarially Trained Model Compression: When Robustness Meets Efficiency. CoRR abs/1902.03538 (2019) - [i33]Hanlin Tang, Xiangru Lian, Tong Zhang, Ji Liu:
DoubleSqueeze: Parallel Stochastic Gradient Descent with Double-Pass Error-Compensated Compression. CoRR abs/1905.05957 (2019) - [i32]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) - [i31]Xiaohan Ding, Guiguang Ding, Xiangxin Zhou, Yuchen Guo, Ji Liu, Jungong Han:
Global Sparse Momentum SGD for Pruning Very Deep Neural Networks. CoRR abs/1909.12778 (2019) - [i30]Shupeng Gui, Xiangliang Zhang, Pan Zhong, Shuang Qiu, Mingrui Wu, Jieping Ye, Zhengdao Wang, Ji Liu:
PINE: Universal Deep Embedding for Graph Nodes via Partial Permutation Invariant Set Functions. CoRR abs/1909.12903 (2019) - [i29]Haichuan Yang, Shupeng Gui, Yuhao Zhu, Ji Liu:
Learning Sparsity and Quantization Jointly and Automatically for Neural Network Compression via Constrained Optimization. CoRR abs/1910.05897 (2019) - [i28]Xingxing Zhang, Shupeng Gui, Zhenfeng Zhu, Yao Zhao, Ji Liu:
ATZSL: Defensive Zero-Shot Recognition in the Presence of Adversaries. CoRR abs/1910.10994 (2019) - [i27]Xingxing Zhang, Shupeng Gui, Zhenfeng Zhu, Yao Zhao, Ji Liu:
Hierarchical Prototype Learning for Zero-Shot Recognition. CoRR abs/1910.11671 (2019) - [i26]Huizhuo Yuan, Xiangru Lian, Ji Liu:
Stochastic Recursive Variance Reduction for Efficient Smooth Non-Convex Compositional Optimization. CoRR abs/1912.13515 (2019) - 2018
- [j22]Bo Liu, Ian Gemp, Mohammad Ghavamzadeh, Ji Liu, Sridhar Mahadevan, Marek Petrik:
Proximal Gradient Temporal Difference Learning: Stable Reinforcement Learning with Polynomial Sample Complexity. J. Artif. Intell. Res. 63: 461-494 (2018) - [j21]Randy Ardywibowo, Shuai Huang, Shupeng Gui, Cao Xiao, Yu Cheng, Ji Liu, Xiaoning Qian:
Switching-State Dynamical Modeling of Daily Behavioral Data. J. Heal. Informatics Res. 2(3): 228-247 (2018) - [j20]Yang Cong, Gan Sun, Ji Liu, Haibin Yu, Jiebo Luo:
User attribute discovery with missing labels. Pattern Recognit. 73: 33-46 (2018) - [j19]Tian Li, Jie Zhong, Ji Liu, Wentao Wu, Ce Zhang:
Ease.ml: Towards Multi-tenant Resource Sharing for Machine Learning Workloads. Proc. VLDB Endow. 11(5): 607-620 (2018) - [j18]Bojan Karlas, Ji Liu, Wentao Wu, Ce Zhang:
Ease.ml in Action: Towards Multi-tenant Declarative Learning Services. Proc. VLDB Endow. 11(12): 2054-2057 (2018) - [j17]Cao Xiao, Yan Jin, Ji Liu, Bo Zeng, Shuai Huang:
Optimal Expert Knowledge Elicitation for Bayesian Network Structure Identification. IEEE Trans Autom. Sci. Eng. 15(3): 1163-1177 (2018) - [j16]Yang Cong, Ji Liu, Baojie Fan, Peng Zeng, Haibin Yu, Jiebo Luo:
Online Similarity Learning for Big Data with Overfitting. IEEE Trans. Big Data 4(1): 78-89 (2018) - [c34]Xiangru Lian, Wei Zhang, Ce Zhang, Ji Liu:
Asynchronous Decentralized Parallel Stochastic Gradient Descent. ICML 2018: 3049-3058 - [c33]Hanlin Tang, Xiangru Lian, Ming Yan, Ce Zhang, Ji Liu:
D2: Decentralized Training over Decentralized Data. ICML 2018: 4855-4863 - [c32]Hanlin Tang, Shaoduo Gan, Ce Zhang, Tong Zhang, Ji Liu:
Communication Compression for Decentralized Training. NeurIPS 2018: 7663-7673 - [i25]Hanlin Tang, Ce Zhang, Shaoduo Gan, Tong Zhang, Ji Liu:
Decentralization Meets Quantization. CoRR abs/1803.06443 (2018) - [i24]Chen Yu, Bojan Karlas, Jie Zhong, Ce Zhang, Ji Liu:
Multi-device, Multi-tenant Model Selection with GP-EI. CoRR abs/1803.06561 (2018) - [i23]Ke Ren, Haichuan Yang, Yu Zhao, Mingshan Xue, Hongyu Miao, Shuai Huang, Ji Liu:
A Robust AUC Maximization Framework with Simultaneous Outlier Detection and Feature Selection for Positive-Unlabeled Classification. CoRR abs/1803.06604 (2018) - [i22]Hanlin Tang, Xiangru Lian, Ming Yan, Ce Zhang, Ji Liu:
D2: Decentralized Training over Decentralized Data. CoRR abs/1803.07068 (2018) - [i21]Zhangyang Wang, Hongyu Xu, Haichuan Yang, Ding Liu, Ji Liu:
Learning Simple Thresholded Features with Sparse Support Recovery. CoRR abs/1804.05515 (2018) - [i20]Shupeng Gui, Xiangliang Zhang, Shuang Qiu, Mingrui Wu, Jieping Ye, Ji Liu:
GESF: A Universal Discriminative Mapping Mechanism for Graph Representation Learning. CoRR abs/1805.11182 (2018) - [i19]Haichuan Yang, Yuhao Zhu, Ji Liu:
End-to-End Learning of Energy-Constrained Deep Neural Networks. CoRR abs/1806.04321 (2018) - [i18]Carson Eisenach, Haichuan Yang, Ji Liu, Han Liu:
Marginal Policy Gradients for Complex Control. CoRR abs/1806.05134 (2018) - [i17]Xiangru Lian, Ji Liu:
Revisit Batch Normalization: New Understanding from an Optimization View and a Refinement via Composition Optimization. CoRR abs/1810.06177 (2018) - [i16]Hanlin Tang, Chen Yu, Cédric Renggli, Simon Kassing, Ankit Singla, Dan Alistarh, Ji Liu, Ce Zhang:
Distributed Learning over Unreliable Networks. CoRR abs/1810.07766 (2018) - [i15]Haichuan Yang, Yuhao Zhu, Ji Liu:
ECC: Energy-Constrained Deep Neural Network Compression via a Bilinear Regression Model. CoRR abs/1812.01803 (2018) - 2017
- [j15]Shupeng Gui, Andrew P. Rice, Rui Chen, Liang Wu, Ji Liu, Hongyu Miao:
A scalable algorithm for structure identification of complex gene regulatory network from temporal expression data. BMC Bioinform. 18(1): 74:1-74:13 (2017) - [j14]Chuyang Ke, Yan Jin, Heather L. Evans, Bill Lober, Xiaoning Qian, Ji Liu, Shuai Huang:
Prognostics of surgical site infections using dynamic health data. J. Biomed. Informatics 65: 22-33 (2017) - [j13]Yijun Huang, Qiang Meng, Heather L. Evans, William B. Lober, Yu Cheng, Xiaoning Qian, Ji Liu, Shuai Huang:
CHI: A contemporaneous health index for degenerative disease monitoring using longitudinal measurements. J. Biomed. Informatics 73: 115-124 (2017) - [j12]Yang Cong, Ji Liu, Gan Sun, Quanzeng You, Yuncheng Li, Jiebo Luo:
Adaptive Greedy Dictionary Selection for Web Media Summarization. IEEE Trans. Image Process. 26(1): 185-195 (2017) - [c31]Xiangru Lian, Mengdi Wang, Ji Liu:
Finite-sum Composition Optimization via Variance Reduced Gradient Descent. AISTATS 2017: 1159-1167 - [c30]Zhangyang Wang, Ji Liu, Shuai Huang, Xinchao Wang, Shiyu Chang:
Transformed Anti-Sparse Hashing. BMVC 2017 - [c29]Haichuan Yang, Shupeng Gui, Chuyang Ke, Daniel Stefankovic, Ryohei Fujimaki, Ji Liu:
On The Projection Operator to A Three-view Cardinality Constrained Set. ICML 2017: 3871-3880 - [c28]Hantian Zhang, Jerry Li, Kaan Kara, Dan Alistarh, Ji Liu, Ce Zhang:
ZipML: Training Linear Models with End-to-End Low Precision, and a Little Bit of Deep Learning. ICML 2017: 4035-4043 - [c27]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 - [i14]Haichuan Yang, Shupeng Gui, Chuyang Ke, Daniel Stefankovic, Ryohei Fujimaki, Ji Liu:
On The Projection Operator to A Three-view Cardinality Constrained Set. CoRR abs/1703.07345 (2017) - [i13]Gan Sun, Yang Cong, Ji Liu, Xiaowei Xu:
Lifelong Metric Learning. CoRR abs/1705.01209 (2017) - [i12]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) - [i11]Tian Li, Jie Zhong, Ji Liu, Wentao Wu, Ce Zhang:
Ease.ml: Towards Multi-tenant Resource Sharing for Machine Learning Workloads. CoRR abs/1708.07308 (2017) - [i10]Xiangru Lian, Wei Zhang, Ce Zhang, Ji Liu:
Asynchronous Decentralized Parallel Stochastic Gradient Descent. CoRR abs/1710.06952 (2017) - 2016
- [j11]Ji Liu, Stephen J. Wright:
An accelerated randomized Kaczmarz algorithm. Math. Comput. 85(297): 153-178 (2016) - [c26]Lam Tran, Deguang Kong, Hongxia Jin, Ji Liu:
Privacy-CNH: A Framework to Detect Photo Privacy with Convolutional Neural Network using Hierarchical Features. AAAI 2016: 1317-1323 - [c25]Deguang Kong, Ji Liu, Bo Liu, Xuan Bao:
Uncorrelated Group LASSO. AAAI 2016: 1765-1771 - [c24]Haichuan Yang, Yijun Huang, Lam Tran, Ji Liu, Shuai Huang:
On Benefits of Selection Diversity via Bilevel Exclusive Sparsity. CVPR 2016: 5945-5954 - [c23]Wei Zhang, Suyog Gupta, Xiangru Lian, Ji Liu:
Staleness-Aware Async-SGD for Distributed Deep Learning. IJCAI 2016: 2350-2356 - [c22]Bo Liu, Ji Liu, Mohammad Ghavamzadeh, Sridhar Mahadevan, Marek Petrik:
Proximal Gradient Temporal Difference Learning Algorithms. IJCAI 2016: 4195-4199 - [c21]Haichuan Yang, Ryohei Fujimaki, Yukitaka Kusumura, Ji Liu:
Online Feature Selection: A Limited-Memory Substitution Algorithm and Its Asynchronous Parallel Variation. KDD 2016: 1945-1954 - [c20]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 - [c19]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 - [i9]Chuyang Ke, Yan Jin, Heather L. Evans, Bill Lober, Xiaoning Qian, Ji Liu, Shuai Huang:
Prognostics of Surgical Site Infections using Dynamic Health Data. CoRR abs/1611.04049 (2016) - [i8]Hantian Zhang, Kaan Kara, Jerry Li, Dan Alistarh, Ji Liu, Ce Zhang:
ZipML: An End-to-end Bitwise Framework for Dense Generalized Linear Models. CoRR abs/1611.05402 (2016) - 2015
- [j10]Ji Liu, Stephen J. Wright, Christopher Ré, Victor Bittorf, Srikrishna Sridhar:
An asynchronous parallel stochastic coordinate descent algorithm. J. Mach. Learn. Res. 16: 285-322 (2015) - [j9]Yang Cong, Shuai Wang, Ji Liu, Jun Cao, Yunsheng Yang, Jiebo Luo:
Deep sparse feature selection for computer aided endoscopy diagnosis. Pattern Recognit. 48(3): 907-917 (2015) - [j8]Ji Liu, Stephen J. Wright:
Asynchronous Stochastic Coordinate Descent: Parallelism and Convergence Properties. SIAM J. Optim. 25(1): 351-376 (2015) - [j7]Yang Cong, Baojie Fan, Ji Liu, Jiebo Luo, Haibin Yu:
Speeded Up Low-Rank Online Metric Learning for Object Tracking. IEEE Trans. Circuits Syst. Video Technol. 25(6): 922-934 (2015) - [c18]Mohammad Iftekhar Tanveer, Ji Liu, Mohammed (Ehsan) Hoque:
Unsupervised Extraction of Human-Interpretable Nonverbal Behavioral Cues in a Public Speaking Scenario. ACM Multimedia 2015: 863-866 - [c17]Xiangru Lian, Yijun Huang, Yuncheng Li, Ji Liu:
Asynchronous Parallel Stochastic Gradient for Nonconvex Optimization. NIPS 2015: 2737-2745 - [c16]Bo Liu, Ji Liu, Mohammad Ghavamzadeh, Sridhar Mahadevan, Marek Petrik:
Finite-Sample Analysis of Proximal Gradient TD Algorithms. UAI 2015: 504-513 - [i7]Xiangru Lian, Yijun Huang, Yuncheng Li, Ji Liu:
Asynchronous Parallel Stochastic Gradient for Nonconvex Optimization. CoRR abs/1506.08272 (2015) - [i6]Yijun Huang, Ji Liu:
Exclusive Sparsity Norm Minimization with Random Groups via Cone Projection. CoRR abs/1510.07925 (2015) - [i5]Wei Zhang, Suyog Gupta, Xiangru Lian, Ji Liu:
Staleness-aware Async-SGD for Distributed Deep Learning. CoRR abs/1511.05950 (2015) - 2014
- [c15]