Optimization and machine learning system (deep learning optimization, stochastic algorithms, asynchronous parallel algorithms, decentralized algorithms, communication efficient algorithms, numerical analysis)
- Hanlin Tang, Xiangru Lian, Ming Yan, Ce Zhang, and Ji Liu, "D2: Decentralized Training over Decentralized Data", ICML, 2018.
- Xiangru Lian, Wei Zhang, Ce Zhang, and Ji Liu, "Asynchronous Decentralized Parallel Stochastic Gradient Descent", ICML, 2018.
- Huoyuan Huo, Bin Gu, Ji Liu, and Heng Huang, "Accelerated Method for Stochastic Composition Optimization with Nonsmooth Regularization", AAAI, 2018.
- Wei Zhang, Xiangru Lian, Ce Zhang, and Ji Liu, "Decentralized Distributed Deep Learning", SOSP workshop on AI systems, 2017.
- Mengdi Wang*, Ji Liu*, and Ethan X. Fang, "Accelerating Stochastic Composition Optimization", Journal of Machine Learning Research, 2017. (* equal contribution.)
- Xiangru Lian, Ce Zhang, Huan Zhang, Cho-Jui Hsieh, Wei Zhang, and Ji Liu, "Can Decentralized Algorithms Outperform Centralized Algorithms? A Case Study for Decentralized Parallel Stochastic Gradient Descent", NIPS 2017 (Oral: rate approximately 1%).
- Wei Zhang, Minwei Feng, Yunhui Zheng, Yufei Ren, Yandong Wang, Ji Liu, Peng Liu, Bing Xiang, Li Zhang, Bowen Zhou, and Fei Wang, "GaDei: On Scale-up Training As A Service For Deep Learning", ICDM, 2017.
- Hantian Zhang, Jerry Li, Kaan Kara, Dan Alistarh, Ji Liu, and Ce Zhang, "The Cans, the Cannots, and a Little Bit of Deep Learning", ICML, 2017. (Oral)
- Xiangru Lian, Mengdi Wang, and Ji Liu, "Finite-sum Composition Optimization via Variance Reduced Gradient Descent", AISTATS, 2017.
- Yang You(*), Xiangru Lian(*), Ji Liu, Hsiang-Fu Yu, Inderjit Dhillon, James Demmel, and Cho-Jui Hsieh, "Asynchronous Parallel Greedy Coordinate Descent", NIPS, 2016. (* equal contribution.)
- Xiangru Lian, Huan Zhang, Cho-Jui Hsieh, Yijun Huang, and Ji Liu, "A Comprehensive Linear Speedup Analysis for Asynchronous Stochastic Parallel Optimization from Zeroth-Order to First-Order", NIPS, 2016. [AsynML package]
- Wei Zhang, Suyog Gupta, Xiangru Lian, and Ji Liu, "Staleness-aware Async-SGD for Distributed Deep Learning", IJCAI, 2016.
- Xiangru Lian, Yijun Huang, Yuncheng Li, and Ji Liu, "Asynchronous Parallel Stochastic Gradient for Nonconvex Optimizations", NIPS, 2015. (Spotlight: rate approximately 4%)
- Isaac Richter, Kamil Pas, Xiaochen Guo, Ravi Patel, Ji Liu, Engin Ipek, and Eby G. Friedman, "Memristive Accelerator for Extreme Scale Linear Solvers", GOMAC, 2015.
- Ji Liu, Stephen J. Wright, Christopher Re, Victor Bittorf, and Srikrishna Sridhar, "An Asynchronous Parallel Stochastic Coordinate Descent Algorithm", Journal of Machine Learning Research, 2015. [AsynML package]
- Ji Liu and Stephen J. Wright, "Asynchronous Stochastic Coordinate Descent: Parallelism and Convergence Properties", arXiv:1403.3862, SIAM on Optimization, 2014. [AsynML package]
- Ji Liu, Stephen J. Wright, Christopher Re, and Victor Bittorf, "An Asynchronous Parallel Stochastic Coordinate Descent Algorithm", ICML, 2014. (Oral) [AsynML package]
- Ji Liu, Stephen J. Wright, and Srikrishna Sridhar, "An Asynchronous Parallel Randomized Kaczmarz Algorithm", arXiv:1401.4780, 2013. [AsynML package]
- Srikrishna Sridhar, Victor Bittorf, Ji Liu, Ce Zhang, Christopher Re, and Stephen J. Wright, "An Approximate, Efficient LP Solver for LP Rounding", NIPS, 2013.
- Ji Liu and Stephen J. Wright, "An Accelerated Randomized Kaczmarz Algorithm", arXiv:1310.2887, 2013.
Reinforcement Learning, bandit problems, and Bayes optimization
- Bojan Karlas, Ji Liu, Wentao Wu, and Ce Zhang"Ease.ml in Action: Towards Multi-tenant Declarative Learning Services/span>", VLDB demo, 2018.
- Tian Li, Jie Zhong, Ji Liu, Wentao Wu, and Ce Zhang, "Ease.ml: Towards Multi-tenant Resource Sharing for Machine Learning Workloads", VLDB, 2017.
- Jie Zhong, Yijun Huang, and Ji Liu, "Asynchronous Parallel Empirical Variance Guided Algorithms for the Thresholding Bandit Problem", 2017.
- Cao Xiao, Yan Jin, Ji Liu, Bo Zeng, and Shuai Huang, "Optimal Expert Knowledge Elicitation for Bayesian Network Structure Identification", IEEE Transactions on Automation Science and Engineering, 2017.
- Mengdi Wang*, Ji Liu*, and Ethan X. Fang, "Accelerating Stochastic Composition Optimization", NIPS, 2016. (* equal contribution.)
- Mengdi Wang and Ji Liu, "A Stochastic Compositional Subgradient Method Using Markov Samples", Informs meeting on WSC, 2016.
- Bo Liu, Luwan Zhang, and Ji Liu, "Dantzig Selector with an Approximately Optimal Denoising Matrix and its Application in Sparse Reinforcement Learning", UAI, 2016.
- Bo Liu, Ji Liu, Mohammad Ghavamzadeh, Sridhar Mahadevan, and Marek Petrik, "Proximal Gradient Temporal Difference Learning Algorithms", IJCAI, 2016. (Invited paper)
- Bo Liu, Ji Liu, Mohammad Ghavamzadeh, Sridhar Mahadevan, and Marek Petrik, "Finite-Sample Analysis of GTD Algorithms", UAI, 2015. (Plenary Presentation, Facebook Best Student Paper award)
- Isaac Richter, Kamil Pas, Xiaochen Guo, Ravi Patel, Ji Liu, Engin Ipek, and Eby G. Friedman, "Memristive Accelerator for Extreme Scale Linear Solvers", GOMAC, 2015.
- Sridhar Mahadevan, Bo Liu, Philip Thomas, Will Dabney, Steve Giguere, Nicholas Jacek, Ian Gemp, Ji Liu, "Proximal Reinforcement Learning: A New Theory of Sequential Decision Making in Primal-Dual Spaces ", 2014.
- Bo Liu, Sridhar Mahadevan, and Ji Liu, Regularized Off-Policy TD-Learning", NIPS, 2012. (Spotlight: rate approximately 4%)
Tensor / matrix completion and decomposition, and missing values
- Jinfeng Yi, Qi Lei, Wesley Gifford, and Ji Liu, "Negative-Unlabeled Tensor Factorization for Location Category Inference from Inaccurate Mobility Data ", ArXiv, 2017
- Gan Sun, Yang Cong, Ji Liu, Jiebo Luo, and Haibin Yu, "User Attribute Discovery with Missing Labels", Pattern Recognition, 2017.
- Zhouyuan Huo, Ji Liu, and Heng Huang, "Optimal Discrete Matrix Completion", AAAI, 2016.
- Ji Liu, Przemyslaw Musialski, Peter Wonka, and Jieping Ye, "Tensor Completion for Estimating Missing Values in Visual Data", ICCV, 2009. [video] [package]
- Ji Liu, Jun Liu, Peter Wonka, and Jieping Ye, "Sparse Non-negative Tensor Factorization Using Columnwise Coordinate Decent", Pattern Recognition, 2012. [package]
- Ji Liu, Przemyslaw Musialski, Peter Wonka, and Jieping Ye, "Tensor Completion for Estimating Missing Values in Visual Data", IEEE Transaction on Pattern Analysis and Machine Intelligence, 2012. [package]
Sparse learning / compressed sensing / feature selection
- Xiaoqian Wang*, Yijun Huang*, Ji Liu, and Heng Huang, "New Balanced Active Learning Model and Optimization Algorithm", IJCAI, 2018. (*equal contribution).
- 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. (Oral)
- Yang Cong, Ji Liu, Baojie Fan, Haibin Yu, and Jiebo Luo, "Online Similarity Learning for Big Data with Overfitting", IEEE Transactions on Big Data, 2017.
- Haichuan Yang, Yukitaka Kusumura, Ryohei Fujimaki, and Ji Liu, "Online Feature Selection: A Limited-Memory Substitution Algorithm and its Asynchronous Parallel Variation", KDD, 2016.
- Haichuan Yang, Yijun Huang, Lam Tran, Ji Liu, and Shuai Huang, "On Benefits of Diversity Selection via Bilevel Exclusive Sparsity", CVPR, 2016.
- Deguang Kong, Ji Liu, Bo Liu and Xuan Bao, "Uncorrelated Group LASSO", AAAI, 2016.
- Yijun Huang and Ji Liu, "Exclusive Sparsity Norm Minimization with Random Groups via Cone Projection", IEEE Transactions on Neural Networks and Learning Systems, 2017 (minor revision).
- Deguang Kong, Ryohei Fujimaki, Ji Liu, Feiping Nie, and Chris Ding, "Exclusive Feature Learning on Arbitrary Structures", NIPS, 2014. (Modified version of NIPS)
- Ji Liu, Ryohei Fujimaki, and Jieping Ye, "Forward-Backward Greedy Algorithms for General Convex Smooth Functions over A Cardinality Constraint", ICML, 2014. (Oral)
- Ji Liu, Lei Yuan, and Jieping Ye, "Dictionary LASSO: Guaranteed Sparse Recovery under Linear Transformation", arXiv:1305.0047v2, 2013.
- Ji Liu, Lei Yuan, and Jieping Ye, "Guaranteed Sparse Recovery under Linear Transformation", ICML, 2013. (Oral)
- Ji Liu, Peter Wonka, and Jieping Ye, "A Multi-stage Framework for Dantzig Selector and Lasso", Journal of Machine Learning Research, 2012.
- Ji Liu and Stephen J. Wright, "Robust Dequantized Compressive Sensing", Applied and Computational Harmonic Analysis, arXiv:1207.0577, 2012.
- Jianhui Chen, Ji Liu, and Jieping Ye, "Learning Incoherent Sparse and Low-Rank Patterns from Multiple Tasks", ACM Transaction on Knowledge Discovery from Data, 2012.
- Jianhui Chen, Ji Liu, and Jieping Ye, "Learning Incoherent Sparse and Low-Rank Patterns from Multiple Tasks", KDD, 2010. (Honorable Mention for the best research paper)
- Ji Liu, Peter Wonka, and Jieping Ye, "Multi-stage Dantzig Selector", NIPS, 2010. [package]
Machine teaching
- Xiaojin Zhu, Ji Liu, and Manuel Lopes, "No Learner Left Behind: On the Complexity of Teaching Multiple Learners Simultaneously", IJCAI, 2017.
- Ji Liu, Xiaojin Zhu, and Hrag Ohannessian, "The Teaching Dimension of Linear Learners", ICML, 2016. (Oral)
- Ji Liu and Xiaojin Zhu, "The Teaching Dimension of Linear Learners", Journal of Machine Learning Research, 2015.
Healthcare and bioinformatics
- Randy Ardywibowo, Shuai Huang, Shupeng Gui, Yu Cheng, Ji Liu, and Xiaoning Qian, "Switching-State Dynamical Modeling of Daily Behavioral Data", Journal of Health Informatics Research, 2018.
- Gan Sun, Yang Cong, Ji Liu, and Xiaowei Xu, "Lifelong Metric Learning", 2017.
- Yijun Huang, Qiang Meng, Heather Evans, Bill Lober, Yu Cheng, Xiaoning Qian, Ji Liu, and Shuai Huang, "CHI: A Contemporaneous Health Index for Degenerative Disease Monitoring using Longitudinal Measurements", Journal of Biomedical Informatics, 2017.
- Chuyang Ke, Yan Jin, Heather Evans, Bill Lober, Xiaoning Qian, Ji Liu, and Shuai Huang, "Prognostics of Surgical Site Infections using Dynamic Health Data", Journal of Biomedical Informatics, 2016.
- Shupeng Gui, Andrew P. Rice, Rui Chen, Liang Wu, Ji Liu, and Hongyu Miao, "A Scalable Algorithm for Structure Identification of Complex Gene Regulatory Network from Temporal Expression Data", BMC Bioinformatics, 2017.
- Yang Cong, Baojie Fan, Ji Liu, Jun Cao, and Jiebo Luo, "Deep Sparse Feature Selection for Computer Aided Endoscopy Diagnosis", Pattern Recognition, 2014.
Computer Vision (abnormal event detection, online metric learning, video analysis, and dictionary learning)
- Zhangyang Wang, Ji Liu, Shuai Huang, Xinchao Wang, and Shiyu Chang, "Tansformed Anti-sparse Hashing", BMVC, 2017.
- Yang Cong, Ji Liu, Gan Sun, Quanzeng You, Yuncheng Li, and Jiebo Luo, "Adaptive Greedy Dictionary Selection for Web Media Summarization", IEEE Transactions on Image Processing, 2016.
- Lam Tran, Deguang Kong, Hong Xia Jin and Ji Liu, "Privacy-CNH: A Framework to Detect Photo Privacy with Convolutional Neural Network using Hierarchical Features", AAAI, 2016.
- M. Iftekhar Tanveer, Ji Liu, and M. Ehsan Hoque, "Unsupervised Extraction of Human-Interpretable Nonverbal Behavioral Cues in a Public Speaking Scenario", ACMMM, 2015.
- Yang Cong, Baojie Fan, Ji Liu, and Jiebo Luo, "Speeded up Low Rank Online Metric Learning for Object Tracking," IEEE Transactions on Circuits and Systems for Video Technology, 2014.
- Maxwell D. Collins, Ji Liu, Jia Xu, Lopamudra Mukherjee, and Vikas Singh, "Spectral Clustering with a Convex Regularizer on Millions of Images," ECCV, 2014.
- Yang Cong, Ji Liu, Junsong Yuan, and Jiebo Luo, "Self-supervised Online Metric Learning with Low Rank Constraint for Scene Categorization", IEEE Transaction on Image Processing, 2013
- Yang Cong, Junsong Yuan, Ji Liu, "Abnormal Event Detection in Crowded Scenes Using Sparse Representation", Pattern Recognition, 2012.
- Yang Cong, Junsong Yuan, Ji Liu, "Sparse Reconstruction Cost for Abnormal Event Detection", CVPR, 2011.
Robotics and 3D vision reconstruction
- Ji Liu, Yang Cong, Yuechao Wang, and Yandong Tang, "Lunar Terrain Reconstruction Based on PDEs Method", ICIP, 2008.
- Ji Liu, Junjian Peng, Yuechao Wang, and Yandong Tang, "A PDEs Method Preserving Boundaries on Dense Disparity Map Reconstruction", VISAPP, 2008.
- Ji Liu, Yuechao Wang, Chuan Zhou, and Yanfeng Geng, "A Navigation Simulation System of Lunar Rover", ICNSC, pp556-561, 2008. [video1][video2]
- Ji Liu, Yuechao Wang, Chuan Zhou, and Yongzhi He, "A Method of Eliminating the Wheel-terrain Interaction Errors in Lunar Rover Simulation", Chinese Journal of System Simulation, 2008.
- Yang Cong, Xiaomao Li, Ji Liu, and YandongTang, "A Stairway Detection Algorithm based on Vision for UGV Stair Climbing", ICNSC, 2008.
- Jujian Peng, Ji Liu, Yanfeng Geng, Jianda Han, and Yandong Tang, "A Dynamic Stereo Matching Method Based on Epipaolar-region", Chinese Journal of Computer engineering, 2008.
- Yanfeng Geng, Kai Kang, Ji Liu, and Hong Wang, "Manufacturing Schedule of Dual-armed Cluster Tools Based on Heuristic Search", ICIT, 2008.
- Yongzhi He, Chuan Zhou, Ji Liu, Dalong Tan, "Research on Movement Simulation for Wheeled Mobile Robot", Chinese Journal of Scientific Instrument, 2007.