default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDLuo Luo
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
2020 – today
- 2024
[c27]Zhuanghua Liu, Luo Luo, Bryan Kian Hsiang Low:
Incremental Quasi-Newton Methods with Faster Superlinear Convergence Rates. AAAI 2024: 14097-14105- [c26]Zhenwei Lin, Jingfan Xia, Qi Deng, Luo Luo:
Decentralized Gradient-Free Methods for Stochastic Non-smooth Non-convex Optimization. AAAI 2024: 17477-17486 - [c25]Lesi Chen, Haishan Ye, Luo Luo:
An Efficient Stochastic Algorithm for Decentralized Nonconvex-Strongly-Concave Minimax Optimization. AISTATS 2024: 1990-1998 - [c24]Yunyan Bai, Yuxing Liu, Luo Luo:
On the Complexity of Finite-Sum Smooth Optimization under the Polyak-Łojasiewicz Condition. ICML 2024 - [c23]Yuxing Liu, Lesi Chen, Luo Luo:
Decentralized Convex Finite-Sum Optimization with Better Dependence on Condition Numbers. ICML 2024 - [c22]Zhuanghua Liu, Cheng Chen, Luo Luo, Bryan Kian Hsiang Low:
Zeroth-Order Methods for Constrained Nonconvex Nonsmooth Stochastic Optimization. ICML 2024 - [i27]Zhuanghua Liu, Luo Luo, Bryan Kian Hsiang Low:
Incremental Quasi-Newton Methods with Faster Superlinear Convergence Rates. CoRR abs/2402.02359 (2024) - [i26]Yunyan Bai, Yuxing Liu, Luo Luo:
On the Complexity of Finite-Sum Smooth Optimization under the Polyak-Łojasiewicz Condition. CoRR abs/2402.02569 (2024) - [i25]Qihao Zhou, Haishan Ye, Luo Luo:
Near-Optimal Distributed Minimax Optimization under the Second-Order Similarity. CoRR abs/2405.16126 (2024) - [i24]Zhiling Zhou, Zhuanghua Liu, Chengchang Liu, Luo Luo:
Incremental Gauss-Newton Methods with Superlinear Convergence Rates. CoRR abs/2407.03195 (2024) - 2023
- [j7]Haishan Ye, Luo Luo, Ziang Zhou, Tong Zhang:
Multi-Consensus Decentralized Accelerated Gradient Descent. J. Mach. Learn. Res. 24: 306:1-306:50 (2023) - [c21]Lesi Chen, Jing Xu, Luo Luo:
Faster Gradient-Free Algorithms for Nonsmooth Nonconvex Stochastic Optimization. ICML 2023: 5219-5233 - [c20]Chengchang Liu
, Lesi Chen, Luo Luo, John C. S. Lui:
Communication Efficient Distributed Newton Method with Fast Convergence Rates. KDD 2023: 1406-1416 - [c19]Chengchang Liu, Cheng Chen, Luo Luo, John C. S. Lui:
Block Broyden's Methods for Solving Nonlinear Equations. NeurIPS 2023 - [i23]Lesi Chen, Jing Xu, Luo Luo:
Faster Gradient-Free Algorithms for Nonsmooth Nonconvex Stochastic Optimization. CoRR abs/2301.06428 (2023) - [i22]Haikuo Yang, Luo Luo, Chris Junchi Li, Michael I. Jordan:
Accelerating Inexact HyperGradient Descent for Bilevel Optimization. CoRR abs/2307.00126 (2023) - [i21]Lesi Chen, Boyuan Yao, Luo Luo:
Faster Stochastic Algorithms for Minimax Optimization under Polyak-Łojasiewicz Conditions. CoRR abs/2307.15868 (2023) - [i20]Zhenwei Lin, Jingfan Xia, Qi Deng, Luo Luo:
Decentralized Gradient-Free Methods for Stochastic Non-Smooth Non-Convex Optimization. CoRR abs/2310.11973 (2023) - 2022
- [c18]Chengchang Liu, Shuxian Bi, Luo Luo, John C. S. Lui:
Partial-Quasi-Newton Methods: Efficient Algorithms for Minimax Optimization Problems with Unbalanced Dimensionality. KDD 2022: 1031-1041 - [c17]Lesi Chen, Boyuan Yao, Luo Luo:
Faster Stochastic Algorithms for Minimax Optimization under Polyak-{\L}ojasiewicz Condition. NeurIPS 2022 - [c16]Chengchang Liu, Luo Luo:
Quasi-Newton Methods for Saddle Point Problems. NeurIPS 2022 - [c15]Luo Luo, Yujun Li, Cheng Chen:
Finding Second-Order Stationary Points in Nonconvex-Strongly-Concave Minimax Optimization. NeurIPS 2022 - [i19]Luo Luo, Haishan Ye:
Decentralized Stochastic Variance Reduced Extragradient Method. CoRR abs/2202.00509 (2022) - [i18]Lesi Chen, Luo Luo:
Near-Optimal Algorithms for Making the Gradient Small in Stochastic Minimax Optimization. CoRR abs/2208.05925 (2022) - [i17]Luo Luo, Haishan Ye:
An Optimal Stochastic Algorithm for Decentralized Nonconvex Finite-sum Optimization. CoRR abs/2210.13931 (2022) - [i16]Lesi Chen, Haishan Ye, Luo Luo:
A Simple and Efficient Stochastic Algorithm for Decentralized Nonconvex-Strongly-Concave Minimax Optimization. CoRR abs/2212.02387 (2022) - 2021
- [j6]Haishan Ye, Luo Luo, Zhihua Zhang:
Approximate Newton Methods. J. Mach. Learn. Res. 22: 66:1-66:41 (2021) - [j5]Haishan Ye, Luo Luo, Zhihua Zhang:
Accelerated Proximal Subsampled Newton Method. IEEE Trans. Neural Networks Learn. Syst. 32(10): 4374-4388 (2021) - [c14]Luo Luo, Cheng Chen, Guangzeng Xie, Haishan Ye:
Revisiting Co-Occurring Directions: Sharper Analysis and Efficient Algorithm for Sparse Matrices. AAAI 2021: 8793-8800 - [i15]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) - [i14]Luo Luo, Cheng Chen:
Finding Second-Order Stationary Point for Nonconvex-Strongly-Concave Minimax Problem. CoRR abs/2110.04814 (2021) - [i13]Chengchang Liu, Luo Luo:
Quasi-Newton Methods for Saddle Point Problems and Beyond. CoRR abs/2111.02708 (2021) - 2020
- [j4]Haishan Ye, Luo Luo, Zhihua Zhang:
Nesterov's Acceleration for Approximate Newton. J. Mach. Learn. Res. 21: 142:1-142:37 (2020) - [c13]Guangzeng Xie, Luo Luo, Yijiang Lian, Zhihua Zhang:
Lower Complexity Bounds for Finite-Sum Convex-Concave Minimax Optimization Problems. ICML 2020: 10504-10513 - [c12]Cheng Chen, Luo Luo, Weinan Zhang, Yong Yu, Yijiang Lian:
Efficient and Robust High-Dimensional Linear Contextual Bandits. IJCAI 2020: 4259-4265 - [c11]Cheng Chen, Luo Luo, Weinan Zhang, Yong Yu:
Efficient Projection-free Algorithms for Saddle Point Problems. NeurIPS 2020 - [c10]Luo Luo, Haishan Ye, Zhichao Huang, Tong Zhang:
Stochastic Recursive Gradient Descent Ascent for Stochastic Nonconvex-Strongly-Concave Minimax Problems. NeurIPS 2020 - [c9]Haishan Ye, Ziang Zhou, Luo Luo, Tong Zhang:
Decentralized Accelerated Proximal Gradient Descent. NeurIPS 2020 - [i12]Luo Luo, Haishan Ye, Tong Zhang:
Stochastic Recursive Gradient Descent Ascent for Stochastic Nonconvex-Strongly-Concave Minimax Problems. CoRR abs/2001.03724 (2020) - [i11]Haishan Ye, Luo Luo, Ziang Zhou, Tong Zhang:
Multi-consensus Decentralized Accelerated Gradient Descent. CoRR abs/2005.00797 (2020) - [i10]Luo Luo, Cheng Chen, Guangzeng Xie, Haishan Ye:
Revisiting Co-Occurring Directions: Sharper Analysis and Efficient Algorithm for Sparse Matrices. CoRR abs/2009.02553 (2020) - [i9]Cheng Chen, Luo Luo, Weinan Zhang, Yong Yu:
Efficient Projection-Free Algorithms for Saddle Point Problems. CoRR abs/2010.11737 (2020)
2010 – 2019
- 2019
- [j3]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) - [j2]Haishan Ye, Guangzeng Xie, Luo Luo, Zhihua Zhang:
Fast stochastic second-order method logarithmic in condition number. Pattern Recognit. 88: 629-642 (2019) - [i8]Guangzeng Xie, Luo Luo, Zhihua Zhang:
A General Analysis Framework of Lower Complexity Bounds for Finite-Sum Optimization. CoRR abs/1908.08394 (2019) - [i7]Luo Luo, Cheng Chen, Yujun Li, Guangzeng Xie, Zhihua Zhang:
A Stochastic Proximal Point Algorithm for Saddle-Point Problems. CoRR abs/1909.06946 (2019) - 2018
- [c8]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
- [c7]Zihao Chen, Luo Luo, Zhihua Zhang:
Communication Lower Bounds for Distributed Convex Optimization: Partition Data on Features. AAAI 2017: 1812-1818 - [c6]Haishan Ye, Luo Luo, Zhihua Zhang:
Approximate Newton Methods and Their Local Convergence. ICML 2017: 3931-3939 - [i6]Haishan Ye, Luo Luo, Zhihua Zhang:
A Unifying Framework for Convergence Analysis of Approximate Newton Methods. CoRR abs/1702.08124 (2017) - [i5]Luo Luo, Cheng Chen, Zhihua Zhang, Wu-Jun Li:
Online Learning Via Regularized Frequent Directions. CoRR abs/1705.05067 (2017) - 2016
- [j1]Shusen Wang, Luo Luo, Zhihua Zhang:
SPSD Matrix Approximation vis Column Selection: Theories, Algorithms, and Extensions. J. Mach. Learn. Res. 17: 49:1-49:49 (2016) - [c5]Qiaomin Ye, Luo Luo, Zhihua Zhang:
Frequent Direction Algorithms for Approximate Matrix Multiplication with Applications in CCA. IJCAI 2016: 2301-2307 - [c4]Tianfan Fu, Luo Luo, Zhihua Zhang:
Quasi-Newton Hamiltonian Monte Carlo. UAI 2016 - [i4]Luo Luo, Zihao Chen, Zhihua Zhang, Wu-Jun Li:
Variance-Reduced Second-Order Methods. CoRR abs/1602.00223 (2016) - [i3]Haishan Ye, Luo Luo, Zhihua Zhang:
Revisiting Sub-sampled Newton Methods. CoRR abs/1608.02875 (2016) - [i2]Zihao Chen, Luo Luo, Zhihua Zhang:
Communication Lower Bounds for Distributed Convex Optimization: Partition Data on Features. CoRR abs/1612.00599 (2016) - 2015
- [c3]Luo Luo, Yubo Xie, Zhihua Zhang, Wu-Jun Li:
Support Matrix Machines. ICML 2015: 938-947 - 2014
- [i1]Shusen Wang, Luo Luo, Zhihua Zhang:
The Modified Nystrom Method: Theories, Algorithms, and Extension. CoRR abs/1406.5675 (2014) - 2013
- [c2]Zhiquan Liu, Luo Luo, Wu-Jun Li:
Robust crowdsourced learning. IEEE BigData 2013: 338-343
2000 – 2009
- 2008
- [c1]Joanne McGrath Cohoon, Zhen Wu, Luo Luo:
Will they stay or will they go? SIGCSE 2008: 397-401
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 02:26 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:
