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ORCIDBelhal Karimi
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2020 – today
- 2023
[c12]Belhal Karimi, Ping Li, Xiaoyun Li:
Fed-LAMB: Layer-wise and Dimension-wise Locally Adaptive Federated Learning. UAI 2023: 1037-1046- [i11]Belhal Karimi, Jianwen Xie, Ping Li:
STANLEY: Stochastic Gradient Anisotropic Langevin Dynamics for Learning Energy-Based Models. CoRR abs/2310.12667 (2023) - 2022
- [c11]Xiangyi Chen, Belhal Karimi, Weijie Zhao, Ping Li:
On the Convergence of Decentralized Adaptive Gradient Methods. ACML 2022: 217-232 - [c10]Belhal Karimi, Hoi-To Wai, Eric Moulines, Ping Li:
Minimization by Incremental Stochastic Surrogate Optimization for Large Scale Nonconvex Problems. ALT 2022: 606-637 - [c9]Weijie Zhao, Xuewu Jiao, Xinsheng Luo, Jingxue Li, Belhal Karimi, Ping Li:
FeatureBox: Feature Engineering on GPUs for Massive-Scale Ads Systems. IEEE Big Data 2022: 2461-2466 - [c8]Xiaoyun Li, Belhal Karimi, Ping Li:
On Distributed Adaptive Optimization with Gradient Compression. ICLR 2022 - [c7]Hao Li, Xu Li, Belhal Karimi, Jie Chen, Mingming Sun:
Joint Learning of Object Graph and Relation Graph for Visual Question Answering. ICME 2022: 1-6 - [c6]Shaogang Ren, Belhal Karimi, Dingcheng Li, Ping Li:
Variational Flow Graphical Model. KDD 2022: 1493-1503 - [i10]Belhal Karimi, Ping Li:
A Class of Two-Timescale Stochastic EM Algorithms for Nonconvex Latent Variable Models. CoRR abs/2203.10186 (2022) - [i9]Hao Li, Xu Li, Belhal Karimi, Jie Chen, Mingming Sun:
Joint learning of object graph and relation graph for visual question answering. CoRR abs/2205.04188 (2022) - [i8]Xiaoyun Li, Belhal Karimi, Ping Li:
On Distributed Adaptive Optimization with Gradient Compression. CoRR abs/2205.05632 (2022) - [i7]Shaogang Ren, Belhal Karimi, Dingcheng Li, Ping Li:
Variational Flow Graphical Model. CoRR abs/2207.02722 (2022) - [i6]Weijie Zhao, Xuewu Jiao, Xinsheng Luo, Jingxue Li, Belhal Karimi, Ping Li:
FeatureBox: Feature Engineering on GPUs for Massive-Scale Ads Systems. CoRR abs/2210.07768 (2022) - 2021
- [c5]Jun-Kun Wang, Xiaoyun Li, Belhal Karimi, Ping Li:
An Optimistic Acceleration of AMSGrad for Nonconvex Optimization. ACML 2021: 422-437 - [c4]Belhal Karimi, Ping Li:
Two-Timescale Stochastic EM Algorithms. ISIT 2021: 890-895 - [i5]Xiangyi Chen, Belhal Karimi, Weijie Zhao, Ping Li:
On the Convergence of Decentralized Adaptive Gradient Methods. CoRR abs/2109.03194 (2021) - [i4]Belhal Karimi, Xiaoyun Li, Ping Li:
Fed-LAMB: Layerwise and Dimensionwise Locally Adaptive Optimization Algorithm. CoRR abs/2110.00532 (2021) - 2020
- [j1]Belhal Karimi, Marc Lavielle, Eric Moulines:
f-SAEM: A fast stochastic approximation of the EM algorithm for nonlinear mixed effects models. Comput. Stat. Data Anal. 141: 123-138 (2020) - [c3]Yingxue Zhou, Belhal Karimi, Jinxing Yu, Zhiqiang Xu, Ping Li:
Towards Better Generalization of Adaptive Gradient Methods. NeurIPS 2020 - [i3]Farzin Haddadpour, Belhal Karimi, Ping Li, Xiaoyun Li:
FedSKETCH: Communication-Efficient and Private Federated Learning via Sketching. CoRR abs/2008.04975 (2020)
2010 – 2019
- 2019
- [c2]Belhal Karimi, Blazej Miasojedow
, Eric Moulines, Hoi-To Wai:
Non-asymptotic Analysis of Biased Stochastic Approximation Scheme. COLT 2019: 1944-1974 - [c1]Belhal Karimi, Hoi-To Wai, Eric Moulines, Marc Lavielle:
On the Global Convergence of (Fast) Incremental Expectation Maximization Methods. NeurIPS 2019: 2833-2843 - [i2]Belhal Karimi, Blazej Miasojedow, Eric Moulines, Hoi-To Wai:
Non-asymptotic Analysis of Biased Stochastic Approximation Scheme. CoRR abs/1902.00629 (2019) - [i1]Belhal Karimi, Hoi-To Wai, Eric Moulines, Marc Lavielle:
On the Global Convergence of (Fast) Incremental Expectation Maximization Methods. CoRR abs/1910.12521 (2019)
Coauthor Index
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