Repository files navigation Awesome-Coreset-Selection
DeepCore: A Comprehensive Library for Coreset Selection in Deep Learning (arXiv 2022) PDF
Introduction to Core-sets: an Updated Survey (arXiv 2020) PDF
Coresets-methods and history: A theoreticians design pattern for approximation and streaming algorithms (KI-Künstliche Intelligenz 2018) PDF
Coresets and sketches (arXiv 2016) PDF
Efficient Model Training (fast & scalable)
Face-NMS: A Core-set Selection Approach for Efficient Face Recognition (arXiv 2021) PDF
Learning Fast Sample Re-weighting Without Reward Data (arXiv 2021) PDF Code
Submodular Mutual Information for Targeted Data Subset Selection(arXiv 2021) PDF
PRISM: A Unified Framework of Parameterized Submodular Information Measures for Targeted Data Subset Selection and Summarization(arXiv 2021) PDF
Dataset Condensation with Differentiable Siamese Augmentation(ICML 2021) PDF
Coresets for Classification -- Simplified and Strengthened(arXiv 2021) PDF
GRAD-MATCH: Gradient Matching based Data Subset Selection for Efficient Deep Model Training(ICML 2021) PDF Code
GLISTER: Generalization Based Data Subset Selection for Efficient and Robust Learning(AAAI 2021) PDF Code
SVP-CF: Selection via Proxy for Collaborative Filtering Data(arXiv 2021) PDF
Dataset Condensation with Gradient Matching(ICLR 2021) PDF
Deep Learning on a Data Diet: Finding Important Examples Early in Training(arXiv 2021) PDF
A Novel Sequential Coreset Method for Gradient Descent Algorithms(ICML 2021) PDF
Stochastic Subset Selection for Efficient Training and Inference of Neural Networks(ICLR 2021) PDF
Uncovering Coresets for Classification With Multi-Objective Evolutionary Algorithms(arXiv 2020) PDF Code
Coresets for Data-efficient Training of Machine Learning Models(ICML 2020) PDF Code
Selection via Proxy: Efficient Data Selection for Deep Learning (ICLR 2020) PDF Code
Teaching a black-box learner(ICML 2019) PDF
An Empirical Study of Example Forgetting during Deep Neural Network Learning(ICLR 2019) PDF Code
Learning and Data Selection in Big Datasets(ICML 2019) PDF
Preventing Adversarial Use of Datasets through Fair Core-Set Construction(arXiv 2019) PDF
Subset Selection and Summarization in Sequential Data (NeurIPS 2017) PDF
New Frameworks for Offline and Streaming Coreset Constructions (arXiv 2016) PDF
Coresets for k-Segmentation of Streaming Data (NeurIPS 2014) PDF
Online Coreset Selection for Rehearsal-based Continual Learning(arXiv 2021) PDF
Optimal Continual Learning has Perfect Memory and is NP-HARD(ICML 2020) PDF
Coresets via Bilevel Optimization for Continual Learning and Streaming(NeurIPS 2020) PDF Code
Gradient based sample selection for online continual learning(NeurIPS 2019) PDF Code
Active Learning is a Strong Baseline for Data Subset SelectionDownload PDF (NeurIPS 2022 Workshop) PDF Code
Active Learning by Acquiring Contrastive Examples (arXiv 2021) PDF Code
SIMILAR: Submodular Information Measures Based Active Learning In Realistic Scenarios(arXiv 2021) PDF
Contextual Diversity for Active Learning(ECCV 2020) PDF Code
Learning From Less Data: A Unified Data Subset Selection and Active Learning Framework for Computer Vision(WACV 2019) PDF
Bayesian Batch Active Learning as Sparse Subset Approximation(NeurIPS 2019) PDF Code
Active Learning for Convolutional Neural Networks: A Core-Set Approach (ICLR 2018) PDF Code
Adversarial Active Learning for Deep Networks: a Margin Based Approach(arXiv 2018) PDF
Non-Uniform Subset Selection for Active Learning in Structured Data(CVPR 2017) PDF
Submodularity in Data Subset Selection and Active Learning(ICML 2015) PDF
Neural Architecture Search
Core-set Sampling for Efficient Neural Architecture Search (arXiv 2021) PDF
Clustering & Distribution Approximation
Coresets for constrained k-median and k-means clustering in low dimensional Euclidean space (arXiv 2021) PDF
Online Coresets for Clustering with Bregman Divergences(arXiv 2020) PDF
Coresets for Clustering in Graphs of Bounded Treewidth(ICML 2020) PDF
Coresets for Clustering with Fairness Constraints (NeurlPS 2019) PDF Code
Coresets for Ordered Weighted Clustering (ICML 2019) PDF 2018
Strong Coresets for k-Median and Subspace Approximation: Goodbye Dimension(Annual IEEE Symposium on Foundations of Computer Science 2018) PDF
Coresets for Nonparametric Estimation - the Case of DP-Means(ICML 2015) PDF
Distributed Balanced Clustering via Mapping Coresets (NeurlPS 2014) PDF
Super-Samples from Kernel Herding(arXiv 2012) PDF Code
Scalable Training of Mixture Models via Coresets(NeurIPS 2011) PDF
Semi-supervised Batch Active Learning via Bilevel Optimization(ICASSP 2021) PDF Code
RETRIEVE: Coreset Selection for Efficient and Robust Semi-Supervised Learning(NeurIPS 2021) PDF
Extending Contrastive Learning to Unsupervised Coreset Selection(arXiv 2021) PDF
Are all negatives created equal in contrastive instance discrimination? (arXiv 2020) PDF
Robust Data Pruning under Label Noise via Maximizing Re-labeling Accuracy (NeurIPS 2023) PDF
Active label cleaning: Improving dataset quality under resource constraints (arXiv 2021) PDF
Just Train Twice: Improving Group Robustness without Training Group Information(ICML 2021) PDF Code
Coresets for Robust Training of Deep Neural Networks against Noisy Labels(NeurIPS 2020) PDF Code
Small-GAN: Speeding up GAN Training using Core-Sets(ICML 2020) PDF
Bayesian Coresets: Revisiting the Nonconvex Optimization Perspective (AISTATS 2021) PDF Code
Bayesian Pseudocoresets (NeurIPS 2020) PDF Code
Sparse Variational Inference: Bayesian Coresets from Scratch (NeurIPS 2019) PDF Code
Bayesian Coreset Construction via Greedy Iterative Geodesic Ascent(ICML 2018) PDF Code
Training Data Subset Selection for Regression with Controlled Generalization Error(ICML 2021) PDF Code
Coresets for Near-Convex Functions(NeurIPS 2020) PDF
On Coresets for Regularized Regression(ICML 2020) PDF Code
Coresets for Regressions with Panel Data(NeurIPS 2020) PDF Code
Fast Parallel Algorithms for Statistical Subset Selection Problems(NeurIPS 2019) PDF
On Coresets for Logistic Regression(NeurIPS 2018) PDF
Coresets for Scalable Bayesian Logistic Regression (NeurlPS 2016) PDF
SubSetML: Subset Selection in Machine Learning: From Theory to Practice (Workshop @ ICML 2021) Site
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