Han Liu

Orcid: 0000-0002-2470-1755

Affiliations:
  • Northwestern University, Evanston, IL, USA
  • Princeton University, Department of Operations Research and Financial Engineering, NJ, USA
  • Johns Hopkins University, Department of Biostatistics and Computer Science, Baltimore, MD, USA
  • Carnegie Mellon University, Pittsburgh, PA, USA (PhD 2011)
  • University of Toronto, Department of Computer Science, ON, Canada (former)


According to our database1, Han Liu authored at least 116 papers between 2004 and 2023.

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Bibliography

2023
EMS®: A Massive Computational Experiment Management System towards Data-driven Robotics.
Proceedings of the IEEE International Conference on Robotics and Automation, 2023

2022
Learning to Infer Belief Embedded Communication.
CoRR, 2022

Switch Trajectory Transformer with Distributional Value Approximation for Multi-Task Reinforcement Learning.
CoRR, 2022

Reinforcement Learning under a Multi-agent Predictive State Representation Model: Method and Theory.
Proceedings of the Tenth International Conference on Learning Representations, 2022

2021
Robust Scatter Matrix Estimation for High Dimensional Distributions With Heavy Tail.
IEEE Trans. Inf. Theory, 2021

Finite-Sample Analysis for Decentralized Batch Multiagent Reinforcement Learning With Networked Agents.
IEEE Trans. Autom. Control., 2021

RoboFlow: a Data-centric Workflow Management System for Developing AI-enhanced Robots.
Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021

2020
Tensor Graphical Model: Non-Convex Optimization and Statistical Inference.
IEEE Trans. Pattern Anal. Mach. Intell., 2020

Agnostic Estimation for Phase Retrieval.
J. Mach. Learn. Res., 2020

Collision-free Navigation of Human-centered Robots via Markov Games.
Proceedings of the 2020 IEEE International Conference on Robotics and Automation, 2020

Learning to Plan in High Dimensions via Neural Exploration-Exploitation Trees.
Proceedings of the 8th International Conference on Learning Representations, 2020

2019
Symmetry, Saddle Points, and Global Optimization Landscape of Nonconvex Matrix Factorization.
IEEE Trans. Inf. Theory, 2019

Blessing of massive scale: spatial graphical model estimation with a total cardinality constraint approach.
Math. Program., 2019

Efficient, certifiably optimal clustering with applications to latent variable graphical models.
Math. Program., 2019

Layer-Wise Learning Strategy for Nonparametric Tensor Product Smoothing Spline Regression and Graphical Models.
J. Mach. Learn. Res., 2019

Picasso: A Sparse Learning Library for High Dimensional Data Analysis in R and Python.
J. Mach. Learn. Res., 2019

On Fast Convergence of Proximal Algorithms for SQRT-Lasso Optimization: Don't Worry About its Nonsmooth Loss Function.
Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

Grid-Wise Control for Multi-Agent Reinforcement Learning in Video Game AI.
Proceedings of the 36th International Conference on Machine Learning, 2019

2018
Near-optimal stochastic approximation for online principal component estimation.
Math. Program., 2018

Max-norm optimization for robust matrix recovery.
Math. Program., 2018

On Semiparametric Exponential Family Graphical Models.
J. Mach. Learn. Res., 2018

Finite-Sample Analyses for Fully Decentralized Multi-Agent Reinforcement Learning.
CoRR, 2018

Parametrized Deep Q-Networks Learning: Reinforcement Learning with Discrete-Continuous Hybrid Action Space.
CoRR, 2018

Fully Implicit Online Learning.
CoRR, 2018

TStarBots: Defeating the Cheating Level Builtin AI in StarCraft II in the Full Game.
CoRR, 2018

A convex formulation for high-dimensional sparse sliced inverse regression.
CoRR, 2018

Diffusion Approximations for Online Principal Component Estimation and Global Convergence.
CoRR, 2018

Curse of Heterogeneity: Computational Barriers in Sparse Mixture Models and Phase Retrieval.
CoRR, 2018

Exponentially Weighted Imitation Learning for Batched Historical Data.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Sketching Method for Large Scale Combinatorial Inference.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Fully Decentralized Multi-Agent Reinforcement Learning with Networked Agents.
Proceedings of the 35th International Conference on Machine Learning, 2018

Graphical Nonconvex Optimization via an Adaptive Convex Relaxation.
Proceedings of the 35th International Conference on Machine Learning, 2018

The Edge Density Barrier: Computational-Statistical Tradeoffs in Combinatorial Inference.
Proceedings of the 35th International Conference on Machine Learning, 2018

Minimax-Optimal Privacy-Preserving Sparse PCA in Distributed Systems.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017
Post-Regularization Inference for Time-Varying Nonparanormal Graphical Models.
J. Mach. Learn. Res., 2017

On Faster Convergence of Cyclic Block Coordinate Descent-type Methods for Strongly Convex Minimization.
J. Mach. Learn. Res., 2017

Continual Learning in Generative Adversarial Nets.
CoRR, 2017

Homotopy Parametric Simplex Method for Sparse Learning.
CoRR, 2017

Estimating High-dimensional Non-Gaussian Multiple Index Models via Stein's Lemma.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Parametric Simplex Method for Sparse Learning.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

High-dimensional Non-Gaussian Single Index Models via Thresholded Score Function Estimation.
Proceedings of the 34th International Conference on Machine Learning, 2017

2016
Revisiting compressed sensing: exploiting the efficiency of simplex and sparsification methods.
Math. Program. Comput., 2016

Symmetry, Saddle Points, and Global Geometry of Nonconvex Matrix Factorization.
CoRR, 2016

A First Order Free Lunch for SQRT-Lasso.
CoRR, 2016

More Supervision, Less Computation: Statistical-Computational Tradeoffs in Weakly Supervised Learning.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Agnostic Estimation for Misspecified Phase Retrieval Models.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Online ICA: Understanding Global Dynamics of Nonconvex Optimization via Diffusion Processes.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Blind Attacks on Machine Learners.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

A Truth Discovery Approach with Theoretical Guarantee.
Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

Sparse Nonlinear Regression: Parameter Estimation under Nonconvexity.
Proceedings of the 33nd International Conference on Machine Learning, 2016

On the Statistical Limits of Convex Relaxations.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Stochastic Variance Reduced Optimization for Nonconvex Sparse Learning.
Proceedings of the 33nd International Conference on Machine Learning, 2016

An Improved Convergence Analysis of Cyclic Block Coordinate Descent-type Methods for Strongly Convex Minimization.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

Low-Rank and Sparse Structure Pursuit via Alternating Minimization.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

2015
Generalized alternating direction method of multipliers: new theoretical insights and applications.
Math. Program. Comput., 2015

Calibrated multivariate regression with application to neural semantic basis discovery.
J. Mach. Learn. Res., 2015

The flare package for high dimensional linear regression and precision matrix estimation in R.
J. Mach. Learn. Res., 2015

A direct estimation of high dimensional stationary vector autoregressions.
J. Mach. Learn. Res., 2015

Sparse Nonlinear Regression: Parameter Estimation and Asymptotic Inference.
CoRR, 2015

A Nonconvex Optimization Framework for Low Rank Matrix Estimation.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Optimal Linear Estimation under Unknown Nonlinear Transform.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

High Dimensional EM Algorithm: Statistical Optimization and Asymptotic Normality.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Local Smoothness in Variance Reduced Optimization.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Non-convex Statistical Optimization for Sparse Tensor Graphical Model.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Robust Portfolio Optimization.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Robust Estimation of Transition Matrices in High Dimensional Heavy-tailed Vector Autoregressive Processes.
Proceedings of the 32nd International Conference on Machine Learning, 2015

2014
Calibrated Precision Matrix Estimation for High-Dimensional Elliptical Distributions.
IEEE Trans. Inf. Theory, 2014

A Strictly Contractive Peaceman-Rachford Splitting Method for Convex Programming.
SIAM J. Optim., 2014

High Dimensional Semiparametric Scale-Invariant Principal Component Analysis.
IEEE Trans. Pattern Anal. Mach. Intell., 2014

The fastclime package for linear programming and large-scale precision matrix estimation in R.
J. Mach. Learn. Res., 2014

Pathwise Coordinate Optimization for Sparse Learning: Algorithm and Theory.
CoRR, 2014

Nonconvex Statistical Optimization: Minimax-Optimal Sparse PCA in Polynomial Time.
CoRR, 2014

Accelerated Mini-batch Randomized Block Coordinate Descent Method.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Tighten after Relax: Minimax-Optimal Sparse PCA in Polynomial Time.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Multivariate Regression with Calibration.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Sparse PCA with Oracle Property.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Context Aware Group Nearest Shrunken Centroids in Large-Scale Genomic Studies.
Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014

2013
CODA: high dimensional copula discriminant analysis.
J. Mach. Learn. Res., 2013

Optimization for Compressed Sensing: the Simplex Method and Kronecker Sparsification.
CoRR, 2013

Sparse Inverse Covariance Estimation with Calibration.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Robust Sparse Principal Component Regression under the High Dimensional Elliptical Model.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Principal Component Analysis on non-Gaussian Dependent Data.
Proceedings of the 30th International Conference on Machine Learning, 2013

Transition Matrix Estimation in High Dimensional Time Series.
Proceedings of the 30th International Conference on Machine Learning, 2013

Sparse Principal Component Analysis for High Dimensional Multivariate Time Series.
Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, 2013

2012
The huge Package for High-dimensional Undirected Graph Estimation in R.
J. Mach. Learn. Res., 2012

Sparse Additive Machine.
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Sparse Nonparametric Graphical Models
CoRR, 2012

The Nonparanormal SKEPTIC.
CoRR, 2012

Smooth-projected Neighborhood Pursuit for High-dimensional Nonparanormal Graph Estimation.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Exponential Concentration for Mutual Information Estimation with Application to Forests.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Transelliptical Graphical Models.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Transelliptical Component Analysis.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Semiparametric Principal Component Analysis.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

High Dimensional Semiparametric Gaussian Copula Graphical Models.
Proceedings of the 29th International Conference on Machine Learning, 2012

2011
Forest Density Estimation.
J. Mach. Learn. Res., 2011

2010
Nonparametric Learning in High Dimensions.
PhD thesis, 2010

Stability Approach to Regularization Selection (StARS) for High Dimensional Graphical Models.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Graph-Valued Regression.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Forest Density Estimation.
Proceedings of the COLT 2010, 2010

2009
The Nonparanormal: Semiparametric Estimation of High Dimensional Undirected Graphs.
J. Mach. Learn. Res., 2009

A Framework for Efficient Association Rule Mining in XML Data.
Proceedings of the Database Technologies: Concepts, 2009

2008
Nonparametric regression and classification with joint sparsity constraints.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

2007
Sparse Nonparametric Density Estimation in High Dimensions Using the Rodeo.
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics, 2007

SpAM: Sparse Additive Models.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

2006
A Framework for Efficient Association Rule Mining in XML Data.
J. Database Manag., 2006

2005
D-GridMST: Clustering Large Distributed Spatial Databases.
Proceedings of the Classification and Clustering for Knowledge Discovery, 2005

XAR-miner: efficient association rules mining for XML data.
Proceedings of the 14th international conference on World Wide Web, 2005

X-warehouse: building query pattern-driven data.
Proceedings of the 14th international conference on World Wide Web, 2005

2004
A robot path planning approach based on generalized semi-infinite optimization.
Proceedings of the 2004 IEEE Conference on Robotics, Automation and Mechatronics, 2004

An Effective and Efficient Data Cleaning Technique in Large Databases.
Proceedings of the International Conference on Information and Knowledge Engineering. IKE'04, 2004

Generalized Semi-Infinite Optimization and its Application in Robotics' Path Planning Problem.
Proceedings of the International Conference on Artificial Intelligence, 2004

Statistical Issues with Labeled Sample Size Analysis for Semi-Supervised Linear Discriminant Analysis.
Proceedings of the International Conference on Artificial Intelligence, 2004

A Novel Dimensionality Reduction Technique Based on Independent Component Analysis for Modeling Microarray Gene Expression Data.
Proceedings of the International Conference on Artificial Intelligence, 2004

An Efficient Method to Estimate Labelled Sample Size for Transductive LDA(QDA/MDA) Based on Bayes Risk.
Proceedings of the Machine Learning: ECML 2004, 2004

On Efficient and Effective Association Rule Mining from XML Data.
Proceedings of the Database and Expert Systems Applications, 15th International Conference, 2004

PC-Filter: A Robust Filtering Technique for Duplicate Record Detection in Large Databases.
Proceedings of the Database and Expert Systems Applications, 15th International Conference, 2004


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