default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDZhihua Zhang 0004
Person information
- affiliation: Peking University, Center for Statistical Science, School of Mathematical Sciences, China
Other persons with the same name
- Zhihua Zhang (aka: Zhi-Hua Zhang) — disambiguation page
- Zhihua Zhang 0001
![[0000-0002-9387-7308]](https://dblp.org/img/orcid-mark.12x12.png "0000-0002-9387-7308")
— Kaiserslautern University of Technology, Germany - Zhihua Zhang 0002 — Nara Institute of Science and Technology, Nara, Japan (and 1 more)
- Zhihua Zhang 0003 — Shandong University, Interdisciplinary Data Mining Group, School of Mathematics, Jinan, China
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
2020 – today
- 2023
[c28]Xiang Li, Wenhao Yang, Jiadong Liang, Zhihua Zhang, Michael I. Jordan:
A Statistical Analysis of Polyak-Ruppert Averaged Q-Learning. AISTATS 2023: 2207-2261- [c27]Jiadong Liang, Yuze Han, Xiang Li, Zhihua Zhang:
Complete Asymptotic Analysis for Projected Stochastic Approximation and Debiased Variants. Allerton 2023: 1 - 2022
- [c26]Xiang Li, Jiadong Liang, Xiangyu Chang, Zhihua Zhang:
Statistical Estimation and Online Inference via Local SGD. COLT 2022: 1613-1661 - [c25]Jiadong Liang, Yuze Han, Xiang Li, Zhihua Zhang:
Asymptotic Behaviors of Projected Stochastic Approximation: A Jump Diffusion Perspective. NeurIPS 2022 - [c24]Shiyun Lin, Yuze Han, Xiang Li, Zhihua Zhang:
Personalized Federated Learning towards Communication Efficiency, Robustness and Fairness. NeurIPS 2022 - 2021
- [c23]Xiang Li, Shusen Wang, Kun Chen, Zhihua Zhang:
Communication-Efficient Distributed SVD via Local Power Iterations. ICML 2021: 6504-6514 - [i21]Xiang Li, Zhihua Zhang:
Delayed Projection Techniques for Linearly Constrained Problems: Convergence Rates, Acceleration, and Applications. CoRR abs/2101.01505 (2021) - [i20]Xiao Guo, Xiang Li, Xiangyu Chang, Shusen Wang, Zhihua Zhang:
Privacy-Preserving Distributed SVD via Federated Power. CoRR abs/2103.00704 (2021) - [i19]Luo Luo, Guangzeng Xie, Tong Zhang, Zhihua Zhang:
Near Optimal Stochastic Algorithms for Finite-Sum Unbalanced Convex-Concave Minimax Optimization. CoRR abs/2106.01761 (2021) - [i18]Xiang Li, Jiadong Liang, Xiangyu Chang, Zhihua Zhang:
Statistical Estimation and Inference via Local SGD in Federated Learning. CoRR abs/2109.01326 (2021) - [i17]Xiang Li, Wenhao Yang, Zhihua Zhang, Michael I. Jordan:
Polyak-Ruppert Averaged Q-Leaning is Statistically Efficient. CoRR abs/2112.14582 (2021) - 2020
- [c22]Xiang Li, Shusen Wang, Zhihua Zhang:
Do Subsampled Newton Methods Work for High-Dimensional Data? AAAI 2020: 4723-4730 - [c21]Cheng Chen, Ming Gu, Zhihua Zhang, Weinan Zhang, Yong Yu:
Efficient Spectrum-Revealing CUR Matrix Decomposition. AISTATS 2020: 766-775 - [c20]Xiang Li, Kaixuan Huang, Wenhao Yang, Shusen Wang, Zhihua Zhang:
On the Convergence of FedAvg on Non-IID Data. ICLR 2020 - [i16]Xiang Li, Shusen Wang, Kun Chen, Zhihua Zhang:
Communication-Efficient Distributed SVD via Local Power Iterations. CoRR abs/2002.08014 (2020) - [i15]Wenhao Yang, Xiang Li, Guangzeng Xie, Zhihua Zhang:
Finding the Near Optimal Policy via Adaptive Reduced Regularization in MDPs. CoRR abs/2011.00213 (2020)
2010 – 2019
- 2019
- [j11]Luo Luo, Cheng Chen, Zhihua Zhang, Wu-Jun Li, Tong Zhang:
Robust Frequent Directions with Application in Online Learning. J. Mach. Learn. Res. 20: 45:1-45:41 (2019) - [c19]Zhiming Zhou, Jiadong Liang, Yuxuan Song, Lantao Yu, Hongwei Wang, Weinan Zhang, Yong Yu, Zhihua Zhang:
Lipschitz Generative Adversarial Nets. ICML 2019: 7584-7593 - [c18]Wenhao Yang, Xiang Li, Zhihua Zhang:
A Regularized Approach to Sparse Optimal Policy in Reinforcement Learning. NeurIPS 2019: 5938-5948 - [i14]Xiang Li, Shusen Wang, Zhihua Zhang:
Do Subsampled Newton Methods Work for High-Dimensional Data? CoRR abs/1902.04952 (2019) - [i13]Zhiming Zhou, Jiadong Liang, Yuxuan Song, Lantao Yu, Hongwei Wang, Weinan Zhang, Yong Yu, Zhihua Zhang:
Lipschitz Generative Adversarial Nets. CoRR abs/1902.05687 (2019) - [i12]Xiang Li, Wenhao Yang, Zhihua Zhang:
A Unified Framework for Regularized Reinforcement Learning. CoRR abs/1903.00725 (2019) - [i11]Xiang Li, Kaixuan Huang, Wenhao Yang, Shusen Wang, Zhihua Zhang:
On the Convergence of FedAvg on Non-IID Data. CoRR abs/1907.02189 (2019) - [i10]Luo Luo, Cheng Chen, Yujun Li, Guangzeng Xie, Zhihua Zhang:
A Stochastic Proximal Point Algorithm for Saddle-Point Problems. CoRR abs/1909.06946 (2019) - [i9]Xiang Li, Wenhao Yang, Shusen Wang, Zhihua Zhang:
Communication Efficient Decentralized Training with Multiple Local Updates. CoRR abs/1910.09126 (2019) - [i8]Haishan Ye, Shusen Wang, Zhihua Zhang, Tong Zhang:
Fast Generalized Matrix Regression with Applications in Machine Learning. CoRR abs/1912.12008 (2019) - 2018
- [c17]Luo Luo, Wenpeng Zhang, Zhihua Zhang, Wenwu Zhu, Tong Zhang, Jian Pei:
Sketched Follow-The-Regularized-Leader for Online Factorization Machine. KDD 2018: 1900-1909 - 2017
- [j10]Haishan Ye, Yujun Li, Cheng Chen, Zhihua Zhang:
Fast Fisher discriminant analysis with randomized algorithms. Pattern Recognit. 72: 82-92 (2017) - [i7]Luo Luo, Cheng Chen, Zhihua Zhang, Wu-Jun Li:
Online Learning Via Regularized Frequent Directions. CoRR abs/1705.05067 (2017) - 2016
- [j9]Shusen Wang, Zhihua Zhang, Tong Zhang:
Towards More Efficient SPSD Matrix Approximation and CUR Matrix Decomposition. J. Mach. Learn. Res. 17: 210:1-210:49 (2016) - 2015
- [i6]Shusen Wang, Zhihua Zhang, Tong Zhang:
Towards More Efficient Nystrom Approximation and CUR Matrix Decomposition. CoRR abs/1503.08395 (2015) - [i5]Shuang Liu, Cheng Chen, Zhihua Zhang:
Distributed Multi-Armed Bandits: Regret vs. Communication. CoRR abs/1504.03509 (2015) - [i4]Shusen Wang, Zhihua Zhang, Tong Zhang:
Improved Analyses of the Randomized Power Method and Block Lanczos Method. CoRR abs/1508.06429 (2015) - [i3]Cheng Chen, Shuang Liu, Zhihua Zhang, Wu-Jun Li:
A Parallel algorithm for $\mathcal{X}$-Armed bandits. CoRR abs/1510.07471 (2015) - 2014
- [j8]Zhihua Zhang, Cheng Chen, Guang Dai, Wu-Jun Li, Dit-Yan Yeung:
Multicategory large margin classification methods: Hinge losses vs. coherence functions. Artif. Intell. 215: 55-78 (2014) - [i2]Shusen Wang, Tong Zhang, Zhihua Zhang:
Adjusting Leverage Scores by Row Weighting: A Practical Approach to Coherent Matrix Completion. CoRR abs/1412.7938 (2014) - 2012
- [j7]Zhihua Zhang, Shusen Wang, Dehua Liu, Michael I. Jordan:
EP-GIG Priors and Applications in Bayesian Sparse Learning. J. Mach. Learn. Res. 13: 2031-2061 (2012) - [j6]Zhihua Zhang, Dehua Liu, Guang Dai, Michael I. Jordan:
Coherence functions with applications in large-margin classification methods. J. Mach. Learn. Res. 13: 2705-2734 (2012) - [i1]Zhihua Zhang, Michael I. Jordan:
Bayesian Multicategory Support Vector Machines. CoRR abs/1206.6863 (2012) - 2011
- [j5]Zhihua Zhang, Guang Dai, Michael I. Jordan:
Bayesian Generalized Kernel Mixed Models. J. Mach. Learn. Res. 12: 111-139 (2011) - [c16]Wu-Jun Li, Dit-Yan Yeung, Zhihua Zhang:
Generalized Latent Factor Models for Social Network Analysis. IJCAI 2011: 1705-1710 - 2010
- [j4]Zhihua Zhang, Guang Dai, Congfu Xu, Michael I. Jordan:
Regularized Discriminant Analysis, Ridge Regression and Beyond. J. Mach. Learn. Res. 11: 2199-2228 (2010) - [j3]Zhihua Zhang, Gang Wang, Dit-Yan Yeung, Guang Dai, Frederick H. Lochovsky:
A regularization framework for multiclass classification: A deterministic annealing approach. Pattern Recognit. 43(7): 2466-2475 (2010) - [c15]Zhihua Zhang, Guang Dai, Donghui Wang, Michael I. Jordan:
Bayesian Generalized Kernel Models. AISTATS 2010: 972-979 - [c14]Zhihua Zhang, Guang Dai, Michael I. Jordan:
Matrix-Variate Dirichlet Process Mixture Models. AISTATS 2010: 980-987
2000 – 2009
- 2009
- [c13]Wu-Jun Li, Dit-Yan Yeung, Zhihua Zhang:
Probabilistic Relational PCA. NIPS 2009: 1123-1131 - [c12]Zhihua Zhang, Guang Dai, Michael I. Jordan:
A Flexible and Efficient Algorithm for Regularized Fisher Discriminant Analysis. ECML/PKDD (2) 2009: 632-647 - [c11]Wu-Jun Li, Zhihua Zhang, Dit-Yan Yeung:
Latent Wishart Processes for Relational Kernel Learning. AISTATS 2009: 336-343 - [c10]Zhihua Zhang, Michael I. Jordan, Wu-Jun Li, Dit-Yan Yeung:
Coherence Functions for Multicategory Margin-based Classification Methods. AISTATS 2009: 647-654 - [c9]Zhihua Zhang, Michael I. Jordan:
Latent Variable Models for Dimensionality Reduction. AISTATS 2009: 655-662 - 2008
- [c8]Zhihua Zhang, Michael I. Jordan, Dit-Yan Yeung:
Posterior Consistency of the Silverman g-prior in Bayesian Model Choice. NIPS 2008: 1969-1976 - 2007
- [j2]Zhihua Zhang, James T. Kwok, Dit-Yan Yeung:
Surrogate maximization/minimization algorithms and extensions. Mach. Learn. 69(1): 1-33 (2007) - 2006
- [j1]Zhihua Zhang, James T. Kwok, Dit-Yan Yeung:
Model-based transductive learning of the kernel matrix. Mach. Learn. 63(1): 69-101 (2006) - [c7]Zhihua Zhang, Michael I. Jordan:
Bayesian Multicategory Support Vector Machines. UAI 2006 - 2005
- [c6]Gang Wang, Zhihua Zhang, Frederick H. Lochovsky:
Annealed Discriminant Analysis. ECML 2005: 449-460 - [c5]Gang Wang, Hui Zhang, Zhihua Zhang, Frederick H. Lochovsky:
A Bernoulli Relational Model for Nonlinear Embedding. ICDM 2005: 458-465 - 2004
- [c4]Zhihua Zhang, Kap Luk Chan, James T. Kwok, Dit-Yan Yeung:
Bayesian Inference on Principal Component Analysis Using Reversible Jump Markov Chain Monte Carlo. AAAI 2004: 372-377 - [c3]Zhihua Zhang, James T. Kwok, Dit-Yan Yeung:
Surrogate maximization/minimization algorithms for AdaBoost and the logistic regression model. ICML 2004 - [c2]Zhihua Zhang, Dit-Yan Yeung, James T. Kwok:
Bayesian inference for transductive learning of kernel matrix using the Tanner-Wong data augmentation algorithm. ICML 2004 - 2003
- [c1]Zhihua Zhang, James T. Kwok, Dit-Yan Yeung:
Parametric Distance Metric Learning with Label Information. IJCAI 2003: 1450-
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-10-07 21:22 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
