• 2428 Citations
20042020
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Research Output 2004 2019

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Conference article
2018

Exponentially weighted imitation learning for batched historical data

Wang, Q., Xiong, J., Han, L., Sun, P., Liu, H. & Zhang, T., Jan 1 2018, In : Advances in Neural Information Processing Systems. 2018-December, p. 6288-6297 10 p.

Research output: Contribution to journalConference article

Reinforcement learning
Simulators
Trajectories

Sketching method for large scale combinatorial inference

Sun, W. W., Lu, J. & Liu, H., Jan 1 2018, In : Advances in Neural Information Processing Systems. 2018-December, p. 10598-10607 10 p.

Research output: Contribution to journalConference article

Screening
Testing
2017

Diffusion approximations for online principal component estimation and global convergence

Li, C. J., Wang, M., Liu, H. & Zhang, T., Jan 1 2017, In : Advances in Neural Information Processing Systems. 2017-December, p. 646-656 11 p.

Research output: Contribution to journalConference article

Principal component analysis
Eigenvalues and eigenfunctions
Markov processes
1 Citation (Scopus)

Learning non-Gaussian multi-index model via second-order Stein's method

Yang, Z., Balasubramanian, K., Wang, Z. & Liu, H., Jan 1 2017, In : Advances in Neural Information Processing Systems. 2017-December, p. 6098-6107 10 p.

Research output: Contribution to journalConference article

Parametric simplex method for sparse learning

Pang, H., Vanderbei, R., Liu, H. & Zhao, T., Jan 1 2017, In : Advances in Neural Information Processing Systems. 2017-December, p. 188-197 10 p.

Research output: Contribution to journalConference article

Linear regression
Discriminant analysis
Linear programming
Costs
Experiments
2016
4 Citations (Scopus)

Agnostic estimation for misspecified phase retrieval models

Neykov, M., Wang, Z. & Liu, H., Jan 1 2016, In : Advances in Neural Information Processing Systems. p. 4096-4104 9 p.

Research output: Contribution to journalConference article

1 Citation (Scopus)

Blind attacks on machine learners

Beatson, A., Wang, Z. & Liu, H., Jan 1 2016, In : Advances in Neural Information Processing Systems. p. 2405-2413 9 p.

Research output: Contribution to journalConference article

More supervision, less computation: Statistical-computational tradeoffs in weakly supervised learning

Yi, X., Wang, Z., Yang, Z., Caramanis, C. & Liu, H., Jan 1 2016, In : Advances in Neural Information Processing Systems. p. 4482-4490 9 p.

Research output: Contribution to journalConference article

Supervised learning
Computational efficiency
Labels
Polynomials
3 Citations (Scopus)

Online ICA: Understanding global dynamics of nonconvex optimization via diffusion processes

Li, C. J., Wang, Z. & Liu, H., Jan 1 2016, In : Advances in Neural Information Processing Systems. p. 4967-4975 9 p.

Research output: Contribution to journalConference article

Independent component analysis
Ordinary differential equations
Markov processes
Tensors
Differential equations
2015
43 Citations (Scopus)

A nonconvex optimization framework for low rank matrix estimation

Zhao, T., Wang, Z. & Liu, H., Jan 1 2015, In : Advances in Neural Information Processing Systems. 2015-January, p. 559-567 9 p.

Research output: Contribution to journalConference article

11 Citations (Scopus)

High dimensional EM algorithm: Statistical optimization and asymptotic normality?

Wang, Z., Gu, Q., Ning, Y. & Liu, H., Jan 1 2015, In : Advances in Neural Information Processing Systems. 2015-January, p. 2521-2529 9 p.

Research output: Contribution to journalConference article

Parameter estimation
Testing
Statistical Models
3 Citations (Scopus)

Local smoothness in variance reduced optimization

Vainsencher, D., Liu, H. & Zhang, T., Jan 1 2015, In : Advances in Neural Information Processing Systems. 2015-January, p. 2179-2187 9 p.

Research output: Contribution to journalConference article

Sampling
5 Citations (Scopus)

Non-convex statistical optimization for sparse tensor graphical model

Sun, W., Wang, Z., Liu, H. & Cheng, G., Jan 1 2015, In : Advances in Neural Information Processing Systems. 2015-January, p. 1081-1089 9 p.

Research output: Contribution to journalConference article

Tensors
Maximum likelihood estimation
Normal distribution
Recovery
10 Citations (Scopus)

Optimal linear estimation under unknown nonlinear transform

Yi, X., Wang, Z., Caramanis, C. & Liu, H., Jan 1 2015, In : Advances in Neural Information Processing Systems. 2015-January, p. 1549-1557 9 p.

Research output: Contribution to journalConference article

Compressed sensing
Linear regression
Statistics
7 Citations (Scopus)

Robust portfolio optimization

Qiu, H., Han, F., Liu, H. & Caffo, B., Jan 1 2015, In : Advances in Neural Information Processing Systems. 2015-January, p. 46-54 9 p.

Research output: Contribution to journalConference article

Statistics
2014
22 Citations (Scopus)

Accelerated mini-batch randomized block coordinate descent method

Zhao, T., Yu, M., Wang, Y., Arora, R. & Liu, H., Jan 1 2014, In : Advances in Neural Information Processing Systems. 4, January, p. 3329-3337 9 p.

Research output: Contribution to journalConference article

Experiments
1 Citation (Scopus)

Context aware group nearest shrunken centroids in large-scale genomic studies

Yang, J., Han, F., Irizarry, R. A. & Liu, H., Jan 1 2014, In : Journal of Machine Learning Research. 33, p. 1051-1059 9 p.

Research output: Contribution to journalConference article

Context-aware
Centroid
Genomics
Genes
Gene
7 Citations (Scopus)

Mode estimation for high dimensional discrete tree graphical models

Chen, C., Liu, H., Metaxas, D. N. & Zhao, T., Jan 1 2014, In : Advances in Neural Information Processing Systems. 2, January, p. 1323-1331 9 p.

Research output: Contribution to journalConference article

12 Citations (Scopus)

Multivariate regression with calibration

Liu, H., Wang, L. & Zhao, T., Jan 1 2014, In : Advances in Neural Information Processing Systems. 1, January, p. 127-135 9 p.

Research output: Contribution to journalConference article

Calibration
Parameter estimation
Brain
Tuning
Computer simulation
11 Citations (Scopus)

Sparse PCA with oracle property

Gu, Q., Wang, Z. & Liu, H., Jan 1 2014, In : Advances in Neural Information Processing Systems. 2, January, p. 1529-1537 9 p.

Research output: Contribution to journalConference article

Hinges
Covariance matrix
Recovery
Experiments
9 Citations (Scopus)

Tighten after relax: Minimax-optimal sparse PCA in polynomial time

Wang, Z., Lu, H. & Liu, H., Jan 1 2014, In : Advances in Neural Information Processing Systems. 4, January, p. 3383-3391 9 p.

Research output: Contribution to journalConference article

Principal component analysis
Polynomials
Statistical methods
2013
2 Citations (Scopus)
Finance
Logistics
Imaging techniques
Experiments

Sparse precision matrix estimation with calibration

Zhao, T. & Liu, H., Jan 1 2013, In : Advances in Neural Information Processing Systems.

Research output: Contribution to journalConference article

Calibration
Parameter estimation
Tuning
3 Citations (Scopus)

Sparse principal component analysis for high dimensional multivariate time series

Wang, Z., Han, F. & Liu, H., Jan 1 2013, In : Journal of Machine Learning Research. 31, p. 48-56 9 p.

Research output: Contribution to journalConference article

Multivariate Time Series
Principal component analysis
Principal Component Analysis
Time series
High-dimensional
2012
1 Citation (Scopus)

Detecting network cliques with radon basis pursuit

Jiang, X., Yao, Y., Liu, H. & Guibas, L., Jan 1 2012, In : Journal of Machine Learning Research. 22, p. 565-573 9 p.

Research output: Contribution to journalConference article

Basis Pursuit
Compressed sensing
Radon
Approximation algorithms
Clique
2 Citations (Scopus)

Marginal regression for multitask learning

Kolar, M. & Liu, H., Jan 1 2012, In : Journal of Machine Learning Research. 22, p. 647-655 9 p.

Research output: Contribution to journalConference article

Multi-task Learning
Regression
Hamming distance
Convex optimization
Variable Selection
6 Citations (Scopus)

Sparse additive machine

Zhao, T. & Liu, H., Jan 1 2012, In : Journal of Machine Learning Research. 22, p. 1435-1443 9 p.

Research output: Contribution to journalConference article

Support vector machines
Oracle Property
Descent Algorithm
Gradient Algorithm
Gradient Descent
34 Citations (Scopus)

Structured sparse canonical correlation analysis

Chen, X., Liu, H. & Carbonell, J. G., Jan 1 2012, In : Journal of Machine Learning Research. 22, p. 199-207 9 p.

Research output: Contribution to journalConference article

Canonical Correlation Analysis
Genes
Penalty
Optimization Algorithm
Primal-dual Algorithm
2010
12 Citations (Scopus)

The group Dantzig selector

Liu, H., Zhang, J., Jiang, X. & Liu, J., Dec 1 2010, In : Journal of Machine Learning Research. 9, p. 461-468 8 p.

Research output: Contribution to journalConference article

Selector
Learning systems
Basis Pursuit
Norm
Sparsity
2009
23 Citations (Scopus)

Estimation consistency of the group lasso and its applications

Liu, H. & Zhang, J., Dec 1 2009, In : Journal of Machine Learning Research. 5, p. 376-383 8 p.

Research output: Contribution to journalConference article

Lasso
Additive Models
Variable Selection
High-dimensional
Non-negative
2007
17 Citations (Scopus)

Sparse nonparametric density estimation in high dimensions using the rodeo

Liu, H., Lafferty, J. & Wasserman, L., Dec 1 2007, In : Journal of Machine Learning Research. 2, p. 283-290 8 p.

Research output: Contribution to journalConference article

Nonparametric Density Estimation
Higher Dimensions
Regularization
Derivatives
Derivative
2004
2 Citations (Scopus)

An efficient method to estimate labelled sample size for transductive LDA(QDA/MDA) based on bayes risk

Liu, H., Yuan, X., Tang, Q. & Kustra, R., Dec 1 2004, In : Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science). 3201, p. 274-285 12 p.

Research output: Contribution to journalConference article

Bayes Risk
Gaussian distribution
Sample Size
Wine
Supervised learning
1 Citation (Scopus)

Modeling protein tandem mass spectrometry data with an extended linear regression strategy

Liu, H., Bonner, A. J. & Emili, A., Dec 1 2004, In : Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings. 26 IV, p. 3055-3059 5 p.

Research output: Contribution to journalConference article

Tandem Mass Spectrometry
Linear regression
Mass spectrometry
Linear Models
Proteins