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Stochastic Optimization with Importance Sampling

13 January 2014

Tong Zhang

Papers citing "Stochastic Optimization with Importance Sampling"

50 / 183 papers shown

Title
A Coreset Selection of Coreset Selection Literature: Introduction and Recent Advances Brian B. Moser Arundhati S. Shanbhag Stanislav Frolov Federico Raue Joachim Folz Andreas Dengel 252 0 0 23 May 2025
A Two-Stage Data Selection Framework for Data-Efficient Model Training on Edge Devices Chen Gong Rui Xing Zhenzhe Zheng Fan Wu 61 0 0 22 May 2025
From Automation to Autonomy in Smart Manufacturing: A Bayesian Optimization Framework for Modeling Multi-Objective Experimentation and Sequential Decision Making Avijit Saha Asru H. Khosravi I. Imtiaz Ahmed Abdullahil Azeem 436 0 0 05 Apr 2025
Randomized Pairwise Learning with Adaptive Sampling: A PAC-Bayes Analysis Sijia Zhou Yunwen Lei Ata Kabán 146 0 0 03 Apr 2025
Rainfall regression from C-band Synthetic Aperture Radar using Multi-Task Generative Adversarial Networks A. Colin R. Husson 55 0 0 05 Nov 2024
Delta: A Cloud-assisted Data Enrichment Framework for On-Device Continual Learning Chen Gong Zhenzhe Zheng Fan Wu Xiaofeng Jia Guihai Chen LMTD FedML 80 3 0 24 Oct 2024
FLOPS: Forward Learning with OPtimal Sampling Tao Ren Zishi Zhang Jinyang Jiang Guanghao Li Zeliang Zhang Mingqian Feng Yijie Peng 146 1 0 08 Oct 2024
Accelerated Markov Chain Monte Carlo Using Adaptive Weighting Scheme Y Samuel Wang Wenyu Chen Shimin Shan 83 0 0 23 Aug 2024
The Entrapment Problem in Random Walk Decentralized Learning Zonghong Liu S. E. Rouayheb Matthew Dwyer 51 1 0 30 Jul 2024
Multiple Importance Sampling for Stochastic Gradient Estimation Corentin Salaün Xingchang Huang Iliyan Georgiev Niloy J. Mitra Gurprit Singh 93 1 0 22 Jul 2024
Outlier-weighed Layerwise Sampling for LLM Fine-tuning Pengxiang Li L. Yin Xiaowei Gao Shiwei Liu 59 10 0 28 May 2024
A Unified Theory of Stochastic Proximal Point Methods without Smoothness Peter Richtárik Abdurakhmon Sadiev Yury Demidovich 85 4 0 24 May 2024
Adaptive Heterogeneous Client Sampling for Federated Learning over Wireless Networks Bing Luo Wenli Xiao Shiqiang Wang Jianwei Huang Leandros Tassiulas FedML 85 7 0 22 Apr 2024
Unsupervised Federated Optimization at the Edge: D2D-Enabled Learning without Labels Satyavrat Wagle Seyyedali Hosseinalipour Naji Khosravan Christopher G. Brinton FedML 62 2 0 15 Apr 2024
Learning to Rebalance Multi-Modal Optimization by Adaptively Masking Subnetworks Yang Yang Hongpeng Pan Qingjun Jiang Yi Tian Xu Jinghui Tang 59 6 0 12 Apr 2024
LISA: Layerwise Importance Sampling for Memory-Efficient Large Language Model Fine-Tuning Boyao Wang Xiang Liu Shizhe Diao Renjie Pi Jipeng Zhang Chi Han Tong Zhang 106 55 0 26 Mar 2024
Understanding the Training Speedup from Sampling with Approximate Losses Rudrajit Das Xi Chen Bertram Ieong Parikshit Bansal Sujay Sanghavi 51 2 0 10 Feb 2024
Frugal Actor-Critic: Sample Efficient Off-Policy Deep Reinforcement Learning Using Unique Experiences Nikhil Kumar Singh Indranil Saha OffRL 35 0 0 05 Feb 2024
Adaptive Sampling for Deep Learning via Efficient Nonparametric Proxies Shabnam Daghaghi Benjamin Coleman Benito Geordie Anshumali Shrivastava 38 0 0 22 Nov 2023
Adaptive Training Distributions with Scalable Online Bilevel Optimization David Grangier Pierre Ablin Awni Y. Hannun 91 10 0 20 Nov 2023
$Computing Approximate $\ell_p$ Sensitivities$ Computing Approximate $\ell_p$ Sensitivities Swati Padmanabhan David P. Woodruff Qiuyi Zhang 82 0 0 07 Nov 2023
Efficient Active Learning Halfspaces with Tsybakov Noise: A Non-convex Optimization Approach Yinan Li Chicheng Zhang 48 1 0 23 Oct 2023
KAKURENBO: Adaptively Hiding Samples in Deep Neural Network Training Truong Thao Nguyen Balazs Gerofi Edgar Josafat Martinez-Noriega Franccois Trahay Mohamed Wahib 56 1 0 16 Oct 2023
Enhanced Federated Optimization: Adaptive Unbiased Sampling with Reduced Variance Dun Zeng Zenglin Xu Yu Pan Xu Luo Qifan Wang Xiaoying Tang FedML 72 1 0 04 Oct 2023
Combating Data Imbalances in Federated Semi-supervised Learning with Dual Regulators Sikai Bai Shuaicheng Li Weiming Zhuang Jie Zhang Song Guo Kunlin Yang Jun Hou Shuai Zhang Junyu Gao Shuai Yi FedML 54 6 0 11 Jul 2023
AdaSelection: Accelerating Deep Learning Training through Data Subsampling Minghe Zhang Chaosheng Dong Jinmiao Fu Tianchen Zhou Jia Liang ... Bo Liu Michinari Momma Bryan Wang Yan Gao Yi Sun 79 3 0 19 Jun 2023
Importance Sparsification for Sinkhorn Algorithm Mengyun Li Jun Yu Tao Li Cheng Meng OT 122 8 0 11 Jun 2023
Importance Sampling for Stochastic Gradient Descent in Deep Neural Networks Thibault Lahire 31 2 0 29 Mar 2023
PA&DA: Jointly Sampling PAth and DAta for Consistent NAS Shunong Lu Yu Hu Longxing Yang Zihao Sun Jilin Mei Jianchao Tan Chengru Song 47 9 0 28 Feb 2023
Client Selection for Federated Bayesian Learning Jiarong Yang Yuan Liu Rahif Kassab FedML 66 12 0 11 Dec 2022
Client Selection in Federated Learning: Principles, Challenges, and Opportunities Lei Fu Huan Zhang Ge Gao Mi Zhang Xin Liu FedML 86 143 0 03 Nov 2022
Preferential Subsampling for Stochastic Gradient Langevin Dynamics Srshti Putcha Christopher Nemeth Paul Fearnhead 50 0 0 28 Oct 2022
DPIS: An Enhanced Mechanism for Differentially Private SGD with Importance Sampling Jianxin Wei Ergute Bao X. Xiao Yifan Yang 90 21 0 18 Oct 2022
Learning to Learn and Sample BRDFs Chen Liu Michael Fischer Tobias Ritschel AI4CE 108 14 0 07 Oct 2022
Adaptively Weighted Data Augmentation Consistency Regularization for Robust Optimization under Concept Shift Yijun Dong Yuege Xie Rachel A. Ward OOD 76 1 0 04 Oct 2022
Amortized Variational Inference: A Systematic Review Ankush Ganguly Sanjana Jain Ukrit Watchareeruetai 82 17 0 22 Sep 2022
To Store or Not? Online Data Selection for Federated Learning with Limited Storage Chen Gong Zhenzhe Zheng Yunfeng Shao Bingshuai Li Fan Wu Guihai Chen 108 19 0 01 Sep 2022
Information FOMO: The unhealthy fear of missing out on information. A method for removing misleading data for healthier models Ethan Pickering T. Sapsis 68 6 0 27 Aug 2022
Adaptive Learning Rates for Faster Stochastic Gradient Methods Samuel Horváth Konstantin Mishchenko Peter Richtárik ODL 56 9 0 10 Aug 2022
Fast Heterogeneous Federated Learning with Hybrid Client Selection Guangyuan Shen D. Gao Duanxiao Song Libin Yang Xukai Zhou Shirui Pan W. Lou Fang Zhou FedML 121 13 0 10 Aug 2022
Adaptive Sketches for Robust Regression with Importance Sampling S. Mahabadi David P. Woodruff Samson Zhou 48 4 0 16 Jul 2022
Pareto Invariant Risk Minimization: Towards Mitigating the Optimization Dilemma in Out-of-Distribution Generalization Yongqiang Chen Kaiwen Zhou Yatao Bian Binghui Xie Bing Wu ... Kaili Ma Han Yang P. Zhao Bo Han James Cheng OOD OODD 82 36 0 15 Jun 2022
Rate-Distortion Theoretic Bounds on Generalization Error for Distributed Learning Romain Chor Abdellatif Zaidi Milad Sefidgaran FedML 83 15 0 06 Jun 2022
DELTA: Diverse Client Sampling for Fasting Federated Learning Lung-Chuang Wang Yongxin Guo Tao R. Lin Xiaoying Tang FedML 115 26 0 27 May 2022
The Effect of Task Ordering in Continual Learning Samuel J. Bell Neil D. Lawrence CLL 87 17 0 26 May 2022
Transformer with Memory Replay R. Liu Barzan Mozafari OffRL 102 4 0 19 May 2022
Federated Learning Under Intermittent Client Availability and Time-Varying Communication Constraints Mónica Ribero H. Vikalo G. Veciana FedML 76 46 0 13 May 2022
ISTRBoost: Importance Sampling Transfer Regression using Boosting Shrey Gupta Jianzhao Bi Yang Liu Avani Wildani 41 0 0 26 Apr 2022
Active Exploration for Neural Global Illumination of Variable Scenes Stavros Diolatzis Julien Philip G. Drettakis 3DV BDL 48 23 0 15 Mar 2022
Tricks and Plugins to GBM on Images and Sequences Biyi Fang J. Utke Diego Klabjan 127 0 0 01 Mar 2022