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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
![[0000-0001-9679-6303]](https://dblp.dagstuhl.de/img/orcid-mark.12x12.png "0000-0001-9679-6303")
— 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
- Ji Liu 0007 — Argonne National Laboratory, USA
- Ji Liu 0008 — ShanghaiTech University, Shanghai, China
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2020 – today
- 2023
[j37]Liu Liu, Ji Liu, Cho-Jui Hsieh, Dacheng Tao:
Stochastically Controlled Compositional Gradient for Composition Problems. IEEE Trans. Neural Networks Learn. Syst. 34(2): 611-622 (2023)- [c73]Shun Lu, Yu Hu, Peihao Wang, Yan Han, Jianchao Tan, Jixiang Li, Sen Yang, Ji Liu:
PINAT: A Permutation INvariance Augmented Transformer for NAS Predictor. AAAI 2023: 8957-8965 - [c72]Yu Shen, Yang Li, Jian Zheng, Wentao Zhang, Peng Yao, Jixiang Li, Sen Yang, Ji Liu, Bin Cui:
ProxyBO: Accelerating Neural Architecture Search via Bayesian Optimization with Zero-Cost Proxies. AAAI 2023: 9792-9801 - [c71]Wentao Zhu, Yufang Huang, Xiufeng Xie, Wenxian Liu, Jincan Deng, Debing Zhang, Zhangyang Wang, Ji Liu:
AutoShot: A Short Video Dataset and State-of-the-Art Shot Boundary Detection. CVPR Workshops 2023: 2238-2247 - [i71]Wentao Zhu, Yufang Huang, Xiufeng Xie, Wenxian Liu, Jincan Deng, Debing Zhang, Zhangyang Wang, Ji Liu:
AutoShot: A Short Video Dataset and State-of-the-Art Shot Boundary Detection. CoRR abs/2304.06116 (2023) - 2022
- [j36]Gan Sun, Yang Cong, Jiahua Dong, Qiang Wang, Lingjuan Lyu, Ji Liu:
Data Poisoning Attacks on Federated Machine Learning. IEEE Internet Things J. 9(13): 11365-11375 (2022) - [j35]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) - [j34]Liu Liu, Ji Liu, Dacheng Tao:
Variance Reduced Methods for Non-Convex Composition Optimization. IEEE Trans. Pattern Anal. Mach. Intell. 44(9): 5813-5825 (2022) - [j33]Yang Li, Yu Shen, Huaijun Jiang, Wentao Zhang, Jixiang Li, Ji Liu, Ce Zhang, Bin Cui:
Hyper-Tune: Towards Efficient Hyper-parameter Tuning at Scale. Proc. VLDB Endow. 15(6): 1256-1265 (2022) - [j32]Yawei Zhao, Shuang Qiu, Kuan Li, Lailong Luo, Jianping Yin, Ji Liu:
Proximal Online Gradient Is Optimum for Dynamic Regret: A General Lower Bound. IEEE Trans. Neural Networks Learn. Syst. 33(12): 7755-7764 (2022) - [c70]Rui Lu, Baigong Zheng, Jiarui Hai, Fei Tao, Zhiyao Duan, Ji Liu:
Progressive Teacher-Student Training Framework for Music Tagging. ICASSP 2022: 3129-3133 - [c69]Shixing Yu, Tianlong Chen, Jiayi Shen, Huan Yuan, Jianchao Tan, Sen Yang, Ji Liu, Zhangyang Wang:
Unified Visual Transformer Compression. ICLR 2022 - [c68]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 - [c67]Lijie Xu, Shuang Qiu, Binhang Yuan, Jiawei Jiang, Cédric Renggli, Shaoduo Gan, Kaan Kara, Guoliang Li, Ji Liu, Wentao Wu, Jieping Ye, Ce Zhang:
In-Database Machine Learning with CorgiPile: Stochastic Gradient Descent without Full Data Shuffle. SIGMOD Conference 2022: 1286-1300 - [c66]Shen Xin, Yuhang Jiao, Cheng Long, Yuguang Wang, Xiaowei Wang, Sen Yang, Ji Liu, Jie Zhang:
Prototype Feature Extraction for Multi-task Learning. WWW 2022: 2472-2481 - [i70]Yang Li, Yu Shen, Huaijun Jiang, Wentao Zhang, Jixiang Li, Ji Liu, Ce Zhang, Bin Cui:
Hyper-Tune: Towards Efficient Hyper-parameter Tuning at Scale. CoRR abs/2201.06834 (2022) - [i69]Wentao Zhu, Hang Shang, Tingxun Lv, Chao Liao, Sen Yang, Ji Liu:
Adversarial Contrastive Self-Supervised Learning. CoRR abs/2202.13072 (2022) - [i68]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) - [i67]Yi Guo, Zhaocheng Liu, Jianchao Tan, Chao Liao, Daqing Chang, Qiang Liu, Sen Yang, Ji Liu, Dongying Kong, Zhi Chen, Chengru Song:
LPFS: Learnable Polarizing Feature Selection for Click-Through Rate Prediction. CoRR abs/2206.00267 (2022) - [i66]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) - [i65]Lijie Xu, Shuang Qiu, Binhang Yuan, Jiawei Jiang, Cédric Renggli, Shaoduo Gan, Kaan Kara, Guoliang Li, Ji Liu, Wentao Wu, Jieping Ye, Ce Zhang:
Stochastic Gradient Descent without Full Data Shuffle. CoRR abs/2206.05830 (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) - [c65]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 - [c64]Wentao Zhu, Tianlong Kong, Shun Lu, Jixiang Li, Dawei Zhang, Feng Deng, Xiaorui Wang, Sen Yang, Ji Liu:
SpeechNAS: Towards Better Trade-Off Between Latency and Accuracy for Large-Scale Speaker Verification. ASRU 2021: 1102-1109 - [c63]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 - [c62]Haoran Wei, Fei Tao, Ji Liu, Sen Yang, Runze Su:
Ensemble Chinese End-to-End Spoken Language Understanding for Abnormal Event Detection from Audio Stream. ICBDT 2021: 1-5 - [c61]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 - [c60]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 - [c59]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 - [c58]Jiayi Shen, Haotao Wang, Shupeng Gui, Jianchao Tan, Zhangyang Wang, Ji Liu:
UMEC: Unified model and embedding compression for efficient recommendation systems. ICLR 2021 - [c57]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 - [c56]Yue He, Yancheng Dong, Peng Cui, Yuhang Jiao, Xiaowei Wang, Ji Liu, Philip S. Yu:
Purify and Generate: Learning Faithful Item-to-Item Graph from Noisy User-Item Interaction Behaviors. KDD 2021: 3002-3010 - [c55]Xuefan Zha, Wentao Zhu, Xun Lv, Sen Yang, Ji Liu:
Shifted Chunk Transformer for Spatio-Temporal Representational Learning. NeurIPS 2021: 11384-11396 - [c54]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 - [c53]Hanlin Tang, Yao Li, Ji Liu, Ming Yan:
ErrorCompensatedX: error compensation for variance reduced algorithms. NeurIPS 2021: 18102-18113 - [i64]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) - [i63]Ji Liu, Ce Zhang:
Distributed Learning Systems with First-order Methods. CoRR abs/2104.05245 (2021) - [i62]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) - [i61]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) - [i60]Hanlin Tang, Yao Li, Ji Liu, Ming Yan:
ErrorCompensatedX: error compensation for variance reduced algorithms. CoRR abs/2108.02102 (2021) - [i59]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) - [i58]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) - [i57]Xuefan Zha, Wentao Zhu, Tingxun Lv, Sen Yang, Ji Liu:
Shifted Chunk Transformer for Spatio-Temporal Representational Learning. CoRR abs/2108.11575 (2021) - [i56]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) - [i55]Wentao Zhu, Tianlong Kong, Shun Lu, Jixiang Li, Dawei Zhang, Feng Deng, Xiaorui Wang, Sen Yang, Ji Liu:
SpeechNAS: Towards Better Trade-off between Latency and Accuracy for Large-Scale Speaker Verification. CoRR abs/2109.08839 (2021) - [i54]Yu Shen, Yang Li, Jian Zheng, Wentao Zhang, Peng Yao, Jixiang Li, Sen Yang, Ji Liu, Bin Cui:
ProxyBO: Accelerating Neural Architecture Search via Bayesian Optimization with Zero-cost Proxies. CoRR abs/2110.10423 (2021) - [i53]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) - [c52]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 - [c51]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 - [c50]Lin Huang, Jianchao Tan, Ji Liu, Junsong Yuan:
Hand-Transformer: Non-Autoregressive Structured Modeling for 3D Hand Pose Estimation. ECCV (25) 2020: 17-33 - [c49]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 - [c48]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 - [c47]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 - [i52]Zhuolin Yang, Zhikuan Zhao, Hengzhi Pei, Boxin Wang, Bojan Karlas, Ji Liu, Heng Guo, Bo Li, Ce Zhang:
End-to-end Robustness for Sensing-Reasoning Machine Learning Pipelines. CoRR abs/2003.00120 (2020) - [i51]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) - [i50]Gan Sun, Yang Cong, Jiahua Dong, Qiang Wang, Ji Liu:
Data Poisoning Attacks on Federated Machine Learning. CoRR abs/2004.10020 (2020) - [i49]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) - [i48]Bo Liu, Sridhar Mahadevan, Ji Liu:
Regularized Off-Policy TD-Learning. CoRR abs/2006.05314 (2020) - [i47]Bo Liu, Ji Liu, Mohammad Ghavamzadeh, Sridhar Mahadevan, Marek Petrik:
Finite-Sample Analysis of GTD Algorithms. CoRR abs/2006.14364 (2020) - [i46]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) - [i45]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) - [i44]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) - [i43]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) - [i42]Haoran Wei, Fei Tao, Runze Su, Sen Yang, Ji Liu:
Ensemble Chinese End-to-End Spoken Language Understanding for Abnormal Event Detection from audio stream. CoRR abs/2010.09235 (2020) - [i41]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) - [i40]Yunjie Zhang, Fei Tao, Xudong Liu, Runze Su, Xiaorong Mei, Weicong Ding, Zhichen Zhao, Lei Yuan, Ji Liu:
Short Video-based Advertisements Evaluation System: Self-Organizing Learning Approach. CoRR abs/2010.12662 (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) - [c46]Chen Yu, Bojan Karlas, Jie Zhong, Ce Zhang, Ji Liu:
AutoML from Service Provider's Perspective: Multi-device, Multi-tenant Model Selection with GP-EI. AISTATS 2019: 2829-2838 - [c45]Xiangru Lian, Ji Liu:
Revisit Batch Normalization: New Understanding and Refinement via Composition Optimization. AISTATS 2019: 3254-3263 - [c44]Aditya R. Bhattacharya, Ji Liu, Shayok Chakraborty:
A Generic Active Learning Framework for Class Imbalance Applications. BMVC 2019: 121 - [c43]Haichuan Yang, Yuhao Zhu, Ji Liu:
ECC: Platform-Independent Energy-Constrained Deep Neural Network Compression via a Bilinear Regression Model. CVPR 2019: 11206-11215 - [c42]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 - [c41]Haichuan Yang, Yuhao Zhu, Ji Liu:
Energy-Constrained Compression for Deep Neural Networks via Weighted Sparse Projection and Layer Input Masking. ICLR (Poster) 2019 - [c40]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 - [c39]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 - [c38]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 - [c37]Yali Du, Lei Han, Meng Fang, Ji Liu, Tianhong Dai, Dacheng Tao:
LIIR: Learning Individual Intrinsic Reward in Multi-Agent Reinforcement Learning. NeurIPS 2019: 4405-4416 - [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 - [i39]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) - [i38]Hanlin Tang, Xiangru Lian, Tong Zhang, Ji Liu:
DoubleSqueeze: Parallel Stochastic Gradient Descent with Double-Pass Error-Compensated Compression. CoRR abs/1905.05957 (2019) - [i37]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) - [i36]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) - [i35]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) - [i34]Chaoyang He, Conghui Tan, Hanlin Tang, Shuang Qiu, Ji Liu:
Central Server Free Federated Learning over Single-sided Trust Social Networks. CoRR abs/1910.04956 (2019) - [i33]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) - [i32]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) - [i31]Xingxing Zhang, Shupeng Gui, Zhenfeng Zhu, Yao Zhao, Ji Liu:
Hierarchical Prototype Learning for Zero-Shot Recognition. CoRR abs/1910.11671 (2019) - [i30]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 - [i29]Hanlin Tang, Ce Zhang, Shaoduo Gan, Tong Zhang, Ji Liu:
Decentralization Meets Quantization. CoRR abs/1803.06443 (2018) - [i28]Chen Yu, Bojan Karlas, Jie Zhong, Ce Zhang, Ji Liu:
Multi-device, Multi-tenant Model Selection with GP-EI. CoRR abs/1803.06561 (2018) - [i27]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) - [i26]Hanlin Tang, Xiangru Lian, Ming Yan, Ce Zhang, Ji Liu:
D2: Decentralized Training over Decentralized Data. CoRR abs/1803.07068 (2018) - [i25]Zhangyang Wang, Hongyu Xu,