Practical Coreset Constructions for Machine Learning

19 March 2017

Olivier Bachem

Papers citing "Practical Coreset Constructions for Machine Learning"

37 / 37 papers shown

Title
Data Selection for ERMs Steve Hanneke Shay Moran Alexander Shlimovich Amir Yehudayoff 36 0 0 20 Apr 2025
Efficient Biological Data Acquisition through Inference Set Design Ihor Neporozhnii Julien Roy Emmanuel Bengio Jason Hartford 48 1 0 25 Oct 2024
Breaking Class Barriers: Efficient Dataset Distillation via Inter-Class Feature Compensator Xin Zhang Jiawei Du Ping Liu Joey Tianyi Zhou DD 63 2 0 13 Aug 2024
No Dimensional Sampling Coresets for Classification M. Alishahi Jeff M. Phillips 42 1 0 07 Feb 2024
REDUCR: Robust Data Downsampling Using Class Priority Reweighting William Bankes George Hughes Ilija Bogunovic Zi Wang 34 3 0 01 Dec 2023
Performance Scaling via Optimal Transport: Enabling Data Selection from Partially Revealed Sources Feiyang Kang H. Just Anit Kumar Sahu R. Jia 61 10 0 05 Jul 2023
A Comprehensive Study on Dataset Distillation: Performance, Privacy, Robustness and Fairness Zongxiong Chen Jiahui Geng Derui Zhu Herbert Woisetschlaeger Qing Li Sonja Schimmler Ruben Mayer Chunming Rong DD 26 9 0 05 May 2023
StyleDiff: Attribute Comparison Between Unlabeled Datasets in Latent Disentangled Space Keisuke Kawano Takuro Kutsuna Ryoko Tokuhisa Akihiro Nakamura Yasushi Esaki 31 0 0 09 Mar 2023
Unified Convergence Theory of Stochastic and Variance-Reduced Cubic Newton Methods El Mahdi Chayti N. Doikov Martin Jaggi ODL 27 5 0 23 Feb 2023
Selective experience replay compression using coresets for lifelong deep reinforcement learning in medical imaging Guangyao Zheng Samson Zhou Vladimir Braverman M. Jacobs V. Parekh OffRL CLL 24 3 0 22 Feb 2023
Data Distillation: A Survey Noveen Sachdeva Julian McAuley DD 47 73 0 11 Jan 2023
Dataset Distillation via Factorization Songhua Liu Kai Wang Xingyi Yang Jingwen Ye Xinchao Wang DD 140 142 0 30 Oct 2022
Compressed Gastric Image Generation Based on Soft-Label Dataset Distillation for Medical Data Sharing Guang Li Ren Togo Takahiro Ogawa Miki Haseyama DD 32 40 0 29 Sep 2022
Adapting to Online Label Shift with Provable Guarantees Yong Bai Yu-Jie Zhang Peng Zhao Masashi Sugiyama Zhi-Hua Zhou OOD 27 25 0 05 Jul 2022
Dataset Distillation by Matching Training Trajectories George Cazenavette Tongzhou Wang Antonio Torralba Alexei A. Efros Jun-Yan Zhu FedML DD 80 366 0 22 Mar 2022
Fast Distributed k-Means with a Small Number of Rounds Tom Hess Ron Visbord Sivan Sabato 26 1 0 31 Jan 2022
Surrogate Likelihoods for Variational Annealed Importance Sampling M. Jankowiak Du Phan BDL 35 13 0 22 Dec 2021
Coresets for Decision Trees of Signals Ibrahim Jubran Ernesto Evgeniy Sanches Shayda I. Newman Dan Feldman 22 17 0 07 Oct 2021
Data Summarization via Bilevel Optimization Zalan Borsos Mojmír Mutný Marco Tagliasacchi Andreas Krause 30 8 0 26 Sep 2021
Adversarial Robustness of Streaming Algorithms through Importance Sampling Vladimir Braverman Avinatan Hassidim Yossi Matias Mariano Schain Sandeep Silwal Samson Zhou AAML OOD 24 38 0 28 Jun 2021
Partial Wasserstein Covering Keisuke Kawano Satoshi Koide Keisuke Otaki 21 3 0 02 Jun 2021
Manipulating SGD with Data Ordering Attacks Ilia Shumailov Zakhar Shumaylov Dmitry Kazhdan Yiren Zhao Nicolas Papernot Murat A. Erdogdu Ross J. Anderson AAML 112 91 0 19 Apr 2021
Soft-Label Anonymous Gastric X-ray Image Distillation Guang Li Ren Togo Takahiro Ogawa Miki Haseyama DD 42 51 0 07 Apr 2021
Towards understanding the power of quantum kernels in the NISQ era Xinbiao Wang Yuxuan Du Yong Luo Dacheng Tao 38 68 0 31 Mar 2021
One Line To Rule Them All: Generating LO-Shot Soft-Label Prototypes Ilia Sucholutsky Nam-Hwui Kim R. Browne Matthias Schonlau VLM 29 6 0 15 Feb 2021
Semi-supervised Batch Active Learning via Bilevel Optimization Zalan Borsos Marco Tagliasacchi Andreas Krause 32 23 0 19 Oct 2020
'Less Than One'-Shot Learning: Learning N Classes From M<N Samples Ilia Sucholutsky Matthias Schonlau VLM 21 42 0 17 Sep 2020
Distilled One-Shot Federated Learning Yanlin Zhou George Pu Xiyao Ma Xiaolin Li D. Wu FedML DD 62 158 0 17 Sep 2020
Coreset Clustering on Small Quantum Computers T. Tomesh P. Gokhale Eric R. Anschuetz Frederic T. Chong 21 26 0 30 Apr 2020
On Coresets for Support Vector Machines M. Tukan Cenk Baykal Dan Feldman Daniela Rus 35 27 0 15 Feb 2020
Small-GAN: Speeding Up GAN Training Using Core-sets Samarth Sinha Hang Zhang Anirudh Goyal Yoshua Bengio Hugo Larochelle Augustus Odena GAN 38 72 0 29 Oct 2019
Distribution Density, Tails, and Outliers in Machine Learning: Metrics and Applications Nicholas Carlini Ulfar Erlingsson Nicolas Papernot OOD OODD 26 62 0 29 Oct 2019
Soft-Label Dataset Distillation and Text Dataset Distillation Ilia Sucholutsky Matthias Schonlau DD 33 131 0 06 Oct 2019
Interpretability with Accurate Small Models Abhishek Ghose Balaraman Ravindran 20 1 0 04 May 2019
Approximating Spectral Clustering via Sampling: a Review Nicolas M Tremblay Andreas Loukas 21 45 0 29 Jan 2019
Data-Dependent Coresets for Compressing Neural Networks with Applications to Generalization Bounds Cenk Baykal Lucas Liebenwein Igor Gilitschenski Dan Feldman Daniela Rus 25 79 0 15 Apr 2018
PASS-GLM: polynomial approximate sufficient statistics for scalable Bayesian GLM inference Jonathan H. Huggins Ryan P. Adams Tamara Broderick 26 32 0 26 Sep 2017