Han Liu

ORCID

Publication Activity (10 Years)

Years Active: 2004-2024
Publications (10 Years): 72

Top Venues

Publications

Guo Ye, Qinjie Lin, Zening Luo, Han Liu
: A Deployment Operating System for Robots. ICRA (2024)
Quanquan Gu, Zhaoran Wang, Han Liu
Sparse PCA with Oracle Property. CoRR (2023)
Qinjie Lin, Guo Ye, Han Liu
EMS®: A Massive Computational Experiment Management System towards Data-driven Robotics. ICRA (2023)
Junwei Lu, Fang Han, Han Liu
Robust Scatter Matrix Estimation for High Dimensional Distributions With Heavy Tail. IEEE Trans. Inf. Theory 67 (8) (2021)
Kaiqing Zhang, Zhuoran Yang, Han Liu, Tong Zhang, Tamer Basar
Finite-Sample Analysis for Decentralized Batch Multiagent Reinforcement Learning With Networked Agents. IEEE Trans. Autom. Control. 66 (12) (2021)
Tuo Zhao, Han Liu, Kathryn Roeder, John Lafferty, Larry A. Wasserman
The huge Package for High-dimensional Undirected Graph Estimation in R. CoRR (2020)
Matey Neykov, Zhaoran Wang, Han Liu
Agnostic Estimation for Phase Retrieval. J. Mach. Learn. Res. 21 (2020)
Jason Ge, Xingguo Li, Haoming Jiang, Han Liu, Tong Zhang, Mengdi Wang, Tuo Zhao
Picasso: A Sparse Learning Library for High Dimensional Data Analysis in R and Python. CoRR (2020)
Xiang Lyu, Will Wei Sun, Zhaoran Wang, Han Liu, Jian Yang, Guang Cheng
Tensor Graphical Model: Non-Convex Optimization and Statistical Inference. IEEE Trans. Pattern Anal. Mach. Intell. 42 (8) (2020)
Xingguo Li, Tuo Zhao, Xiaoming Yuan, Han Liu
The flare Package for High Dimensional Linear Regression and Precision Matrix Estimation in R. CoRR (2020)
Xingguo Li, Haoming Jiang, Jarvis D. Haupt, Raman Arora, Han Liu, Mingyi Hong, Tuo Zhao
On Fast Convergence of Proximal Algorithms for SQRT-Lasso Optimization: Don't Worry About its Nonsmooth Loss Function. UAI (2019)
Xinyang Yi, Zhaoran Wang, Zhuoran Yang, Constantine Caramanis, Han Liu
More Supervision, Less Computation: Statistical-Computational Tradeoffs in Weakly Supervised Learning. CoRR (2019)
Carson Eisenach, Han Liu
Efficient, certifiably optimal clustering with applications to latent variable graphical models. Math. Program. 176 (1-2) (2019)
Jason Ge, Xingguo Li, Haoming Jiang, Han Liu, Tong Zhang, Mengdi Wang, Tuo Zhao
Picasso: A Sparse Learning Library for High Dimensional Data Analysis in R and Python. J. Mach. Learn. Res. 20 (2019)
Ethan X. Fang, Han Liu, Mengdi Wang
Blessing of massive scale: spatial graphical model estimation with a total cardinality constraint approach. Math. Program. 176 (1-2) (2019)
Xingguo Li, Junwei Lu, Raman Arora, Jarvis D. Haupt, Han Liu, Zhaoran Wang, Tuo Zhao
Symmetry, Saddle Points, and Global Optimization Landscape of Nonconvex Matrix Factorization. IEEE Trans. Inf. Theory 65 (6) (2019)
Lei Han, Peng Sun, Yali Du, Jiechao Xiong, Qing Wang, Xinghai Sun, Han Liu, Tong Zhang
Grid-Wise Control for Multi-Agent Reinforcement Learning in Video Game AI. ICML (2019)
Kean Ming Tan, Junwei Lu, Tong Zhang, Han Liu
Layer-Wise Learning Strategy for Nonparametric Tensor Product Smoothing Spline Regression and Graphical Models. J. Mach. Learn. Res. 20 (2019)
Chao-Bing Song, Ji Liu, Han Liu, Yong Jiang, Tong Zhang
Fully Implicit Online Learning. CoRR (2018)
Qing Wang, Jiechao Xiong, Lei Han, Peng Sun, Han Liu, Tong Zhang
Exponentially Weighted Imitation Learning for Batched Historical Data. NeurIPS (2018)
Qiang Sun, Kean Ming Tan, Han Liu, Tong Zhang
Graphical Nonconvex Optimization via an Adaptive Convex Relaxation. ICML (2018)
Kaiqing Zhang, Zhuoran Yang, Han Liu, Tong Zhang, Tamer Basar
Fully Decentralized Multi-Agent Reinforcement Learning with Networked Agents. ICML (2018)
Jiechao Xiong, Qing Wang, Zhuoran Yang, Peng Sun, Lei Han, Yang Zheng, Haobo Fu, Tong Zhang, Ji Liu, Han Liu
Parametrized Deep Q-Networks Learning: Reinforcement Learning with Discrete-Continuous Hybrid Action Space. CoRR (2018)
Jason Ge, Zhaoran Wang, Mengdi Wang, Han Liu
Minimax-Optimal Privacy-Preserving Sparse PCA in Distributed Systems. AISTATS (2018)
Xingguo Li, Jarvis D. Haupt, Junwei Lu, Zhaoran Wang, Raman Arora, Han Liu, Tuo Zhao
Symmetry. Saddle Points, and Global Optimization Landscape of Nonconvex Matrix Factorization. ITA (2018)
Hao Lu, Yuan Cao, Junwei Lu, Han Liu, Zhaoran Wang
The Edge Density Barrier: Computational-Statistical Tradeoffs in Combinatorial Inference. ICML (2018)
Chris Junchi Li, Mengdi Wang, Han Liu, Tong Zhang
Near-optimal stochastic approximation for online principal component estimation. Math. Program. 167 (1) (2018)
Kaiqing Zhang, Zhuoran Yang, Han Liu, Tong Zhang, Tamer Basar
Finite-Sample Analyses for Fully Decentralized Multi-Agent Reinforcement Learning. CoRR (2018)
Zhuoran Yang, Yang Ning, Han Liu
On Semiparametric Exponential Family Graphical Models. J. Mach. Learn. Res. 19 (2018)
Ethan X. Fang, Han Liu, Kim-Chuan Toh, Wen-Xin Zhou
Max-norm optimization for robust matrix recovery. Math. Program. 167 (1) (2018)
Chris Junchi Li, Mengdi Wang, Han Liu, Tong Zhang
Diffusion Approximations for Online Principal Component Estimation and Global Convergence. CoRR (2018)
Wei Sun, Junwei Lu, Han Liu
Sketching Method for Large Scale Combinatorial Inference. NeurIPS (2018)
Kaiqing Zhang, Zhuoran Yang, Han Liu, Tong Zhang, Tamer Basar
Fully Decentralized Multi-Agent Reinforcement Learning with Networked Agents. CoRR (2018)
Peng Sun, Xinghai Sun, Lei Han, Jiechao Xiong, Qing Wang, Bo Li, Yang Zheng, Ji Liu, Yongsheng Liu, Han Liu, Tong Zhang
TStarBots: Defeating the Cheating Level Builtin AI in StarCraft II in the Full Game. CoRR (2018)
Kean Ming Tan, Zhaoran Wang, Tong Zhang, Han Liu, R. Dennis Cook
A convex formulation for high-dimensional sparse sliced inverse regression. CoRR (2018)
Chris Junchi Li, Zhaoran Wang, Han Liu
Online ICA: Understanding Global Dynamics of Nonconvex Optimization via Diffusion Processes. CoRR (2018)
Jianqing Fan, Han Liu, Zhaoran Wang, Zhuoran Yang
Curse of Heterogeneity: Computational Barriers in Sparse Mixture Models and Phase Retrieval. CoRR (2018)
Haotian Pang, Tuo Zhao, Robert J. Vanderbei, Han Liu
Homotopy Parametric Simplex Method for Sparse Learning. CoRR (2017)
Zhuoran Yang, Krishnakumar Balasubramanian, Zhaoran Wang, Han Liu
Estimating High-dimensional Non-Gaussian Multiple Index Models via Stein's Lemma. NIPS (2017)
Zhuoran Yang, Krishnakumar Balasubramanian, Han Liu
High-dimensional Non-Gaussian Single Index Models via Thresholded Score Function Estimation. ICML (2017)
Haotian Pang, Han Liu, Robert J. Vanderbei, Tuo Zhao
Parametric Simplex Method for Sparse Learning. NIPS (2017)
Junwei Lu, Mladen Kolar, Han Liu
Post-Regularization Inference for Time-Varying Nonparanormal Graphical Models. J. Mach. Learn. Res. 18 (2017)
Ari Seff, Alex Beatson, Daniel Suo, Han Liu
Continual Learning in Generative Adversarial Nets. CoRR (2017)
Xingguo Li, Tuo Zhao, Raman Arora, Han Liu, Mingyi Hong
On Faster Convergence of Cyclic Block Coordinate Descent-type Methods for Strongly Convex Minimization. J. Mach. Learn. Res. 18 (2017)
Alex Beatson, Zhaoran Wang, Han Liu
Blind Attacks on Machine Learners. NIPS (2016)
Xingguo Li, Zhaoran Wang, Junwei Lu, Raman Arora, Jarvis D. Haupt, Han Liu, Tuo Zhao
Symmetry, Saddle Points, and Global Geometry of Nonconvex Matrix Factorization. CoRR (2016)
Xingguo Li, Tuo Zhao, Raman Arora, Han Liu, Jarvis D. Haupt
Stochastic Variance Reduced Optimization for Nonconvex Sparse Learning. CoRR (2016)
Zhuoran Yang, Zhaoran Wang, Han Liu, Yonina C. Eldar, Tong Zhang
Sparse Nonlinear Regression: Parameter Estimation under Nonconvexity. ICML (2016)
Zhaoran Wang, Quanquan Gu, Han Liu
On the Statistical Limits of Convex Relaxations. ICML (2016)
Houping Xiao, Jing Gao, Zhaoran Wang, Shiyu Wang, Lu Su, Han Liu
A Truth Discovery Approach with Theoretical Guarantee. KDD (2016)
Xingguo Li, Tuo Zhao, Raman Arora, Han Liu, Jarvis D. Haupt
Stochastic Variance Reduced Optimization for Nonconvex Sparse Learning. ICML (2016)
Robert J. Vanderbei, Kevin Lin, Han Liu, Lie Wang
Revisiting compressed sensing: exploiting the efficiency of simplex and sparsification methods. Math. Program. Comput. 8 (3) (2016)
Xingguo Li, Tuo Zhao, Raman Arora, Han Liu, Mingyi Hong
An Improved Convergence Analysis of Cyclic Block Coordinate Descent-type Methods for Strongly Convex Minimization. CoRR (2016)
Xingguo Li, Tuo Zhao, Raman Arora, Han Liu, Mingyi Hong
An Improved Convergence Analysis of Cyclic Block Coordinate Descent-type Methods for Strongly Convex Minimization. AISTATS (2016)
Quanquan Gu, Zhaoran Wang, Han Liu
Low-Rank and Sparse Structure Pursuit via Alternating Minimization. AISTATS (2016)
Xingguo Li, Jarvis D. Haupt, Raman Arora, Han Liu, Mingyi Hong, Tuo Zhao
A First Order Free Lunch for SQRT-Lasso. CoRR (2016)
Chris Junchi Li, Zhaoran Wang, Han Liu
Online ICA: Understanding Global Dynamics of Nonconvex Optimization via Diffusion Processes. NIPS (2016)
Matey Neykov, Zhaoran Wang, Han Liu
Agnostic Estimation for Misspecified Phase Retrieval Models. NIPS (2016)
Xinyang Yi, Zhaoran Wang, Zhuoran Yang, Constantine Caramanis, Han Liu
More Supervision, Less Computation: Statistical-Computational Tradeoffs in Weakly Supervised Learning. NIPS (2016)
Xingguo Li, Tuo Zhao, Xiaoming Yuan, Han Liu
The flare package for high dimensional linear regression and precision matrix estimation in R. J. Mach. Learn. Res. 16 (2015)
Wei Sun, Zhaoran Wang, Han Liu, Guang Cheng
Non-convex Statistical Optimization for Sparse Tensor Graphical Model. NIPS (2015)
Fang Han, Huanran Lu, Han Liu
A direct estimation of high dimensional stationary vector autoregressions. J. Mach. Learn. Res. 16 (2015)
Zhuoran Yang, Zhaoran Wang, Han Liu, Yonina C. Eldar, Tong Zhang
Sparse Nonlinear Regression: Parameter Estimation and Asymptotic Inference. CoRR (2015)
Daniel Vainsencher, Han Liu, Tong Zhang
Local Smoothness in Variance Reduced Optimization. NIPS (2015)
Han Liu, Lie Wang, Tuo Zhao
Calibrated multivariate regression with application to neural semantic basis discovery. J. Mach. Learn. Res. 16 (2015)
Huitong Qiu, Fang Han, Han Liu, Brian Caffo
Robust Portfolio Optimization. NIPS (2015)
Xinyang Yi, Zhaoran Wang, Constantine Caramanis, Han Liu
Optimal linear estimation under unknown nonlinear transform. CoRR (2015)
Tuo Zhao, Zhaoran Wang, Han Liu
A Nonconvex Optimization Framework for Low Rank Matrix Estimation. NIPS (2015)
Huitong Qiu, Sheng Xu, Fang Han, Han Liu, Brian Caffo
Robust Estimation of Transition Matrices in High Dimensional Heavy-tailed Vector Autoregressive Processes. ICML (2015)
Xinyang Yi, Zhaoran Wang, Constantine Caramanis, Han Liu
Optimal Linear Estimation under Unknown Nonlinear Transform. NIPS (2015)
Zhaoran Wang, Quanquan Gu, Yang Ning, Han Liu
High Dimensional EM Algorithm: Statistical Optimization and Asymptotic Normality. NIPS (2015)
Ethan X. Fang, Bingsheng He, Han Liu, Xiaoming Yuan
Generalized alternating direction method of multipliers: new theoretical insights and applications. Math. Program. Comput. 7 (2) (2015)
Juemin Yang, Fang Han, Rafael A. Irizarry, Han Liu
Context Aware Group Nearest Shrunken Centroids in Large-Scale Genomic Studies. AISTATS (2014)
Fang Han, Han Liu
High Dimensional Semiparametric Scale-Invariant Principal Component Analysis. IEEE Trans. Pattern Anal. Mach. Intell. 36 (10) (2014)
Zhaoran Wang, Huanran Lu, Han Liu
Tighten after Relax: Minimax-Optimal Sparse PCA in Polynomial Time. NIPS (2014)
Haotian Pang, Han Liu, Robert J. Vanderbei
The fastclime package for linear programming and large-scale precision matrix estimation in R. J. Mach. Learn. Res. 15 (1) (2014)
Han Liu, Lie Wang, Tuo Zhao
Multivariate Regression with Calibration. NIPS (2014)
Zhaoran Wang, Huanran Lu, Han Liu
Nonconvex Statistical Optimization: Minimax-Optimal Sparse PCA in Polynomial Time. CoRR (2014)
Bingsheng He, Han Liu, Zhaoran Wang, Xiaoming Yuan
A Strictly Contractive Peaceman-Rachford Splitting Method for Convex Programming. SIAM J. Optim. 24 (3) (2014)
Tuo Zhao, Han Liu, Tong Zhang
Pathwise Coordinate Optimization for Sparse Learning: Algorithm and Theory. CoRR (2014)
Tuo Zhao, Mo Yu, Yiming Wang, Raman Arora, Han Liu
Accelerated Mini-batch Randomized Block Coordinate Descent Method. NIPS (2014)
Tuo Zhao, Han Liu
Calibrated Precision Matrix Estimation for High-Dimensional Elliptical Distributions. IEEE Trans. Inf. Theory 60 (12) (2014)
Quanquan Gu, Zhaoran Wang, Han Liu
Sparse PCA with Oracle Property. NIPS (2014)
Zhaoran Wang, Fang Han, Han Liu
Sparse Principal Component Analysis for High Dimensional Multivariate Time Series. AISTATS (2013)
Tuo Zhao, Han Liu
Sparse Inverse Covariance Estimation with Calibration. NIPS (2013)
Fang Han, Tuo Zhao, Han Liu
CODA: high dimensional copula discriminant analysis. J. Mach. Learn. Res. 14 (1) (2013)
Fang Han, Han Liu
Principal Component Analysis on non-Gaussian Dependent Data. ICML (1) (2013)
Han Liu, Lie Wang, Tuo Zhao
Calibrated Multivariate Regression with Application to Neural Semantic Basis Discovery. CoRR (2013)
Fang Han, Han Liu
Transition Matrix Estimation in High Dimensional Time Series. ICML (2) (2013)
Robert J. Vanderbei, Han Liu, Lie Wang, Kevin Lin
Optimization for Compressed Sensing: the Simplex Method and Kronecker Sparsification. CoRR (2013)
Fang Han, Han Liu
Robust Sparse Principal Component Regression under the High Dimensional Elliptical Model. NIPS (2013)
Han Liu, John D. Lafferty, Larry A. Wasserman
Exponential Concentration for Mutual Information Estimation with Application to Forests. NIPS (2012)
Fang Han, Han Liu
Transelliptical Component Analysis. NIPS (2012)
Tuo Zhao, Kathryn Roeder, Han Liu
Smooth-projected Neighborhood Pursuit for High-dimensional Nonparanormal Graph Estimation. NIPS (2012)
Han Liu, Fang Han, Ming Yuan, John D. Lafferty, Larry A. Wasserman
High Dimensional Semiparametric Gaussian Copula Graphical Models. ICML (2012)
Han Liu, Fang Han, Cun-Hui Zhang
Transelliptical Graphical Models. NIPS (2012)
Tuo Zhao, Han Liu, Kathryn Roeder, John D. Lafferty, Larry A. Wasserman
The huge Package for High-dimensional Undirected Graph Estimation in R. J. Mach. Learn. Res. 13 (2012)
Fang Han, Han Liu
Semiparametric Principal Component Analysis. NIPS (2012)
Tuo Zhao, Han Liu
Sparse Additive Machine. AISTATS (2012)
John D. Lafferty, Han Liu, Larry A. Wasserman
Sparse Nonparametric Graphical Models CoRR (2012)

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Publication Activity (10 Years)

Top Topics

Top Venues

Han Liu