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• 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

• Face-NMS: A Core-set Selection Approach for Efficient Face Recognition (arXiv 2021)PDF
• Learning Fast Sample Re-weighting Without Reward Data (arXiv 2021)PDFCode
• 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)PDFCode
• GLISTER: Generalization Based Data Subset Selection for Efficient and Robust Learning(AAAI 2021)PDFCode
• 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)PDFCode
• Coresets for Data-efficient Training of Machine Learning Models(ICML 2020)PDFCode
• Selection via Proxy: Efficient Data Selection for Deep Learning (ICLR 2020)PDFCode

• Teaching a black-box learner(ICML 2019)PDF
• An Empirical Study of Example Forgetting during Deep Neural Network Learning(ICLR 2019)PDFCode
• 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)PDFCode

• Gradient based sample selection for online continual learning(NeurIPS 2019)PDFCode

• Active Learning is a Strong Baseline for Data Subset SelectionDownload PDF (NeurIPS 2022 Workshop)PDFCode

• Active Learning by Acquiring Contrastive Examples (arXiv 2021)PDFCode
• SIMILAR: Submodular Information Measures Based Active Learning In Realistic Scenarios(arXiv 2021)PDF

• Contextual Diversity for Active Learning(ECCV 2020)PDFCode

• 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)PDFCode

• Active Learning for Convolutional Neural Networks: A Core-Set Approach (ICLR 2018)PDFCode
• 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

• Core-set Sampling for Efficient Neural Architecture Search (arXiv 2021)PDF

• 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)PDFCode
• 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)PDFCode

• Scalable Training of Mixture Models via Coresets(NeurIPS 2011)PDF

• Semi-supervised Batch Active Learning via Bilevel Optimization(ICASSP 2021)PDFCode
• 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)PDFCode

• Coresets for Robust Training of Deep Neural Networks against Noisy Labels(NeurIPS 2020)PDFCode

• Small-GAN: Speeding up GAN Training using Core-Sets(ICML 2020)PDF

• Bayesian Coresets: Revisiting the Nonconvex Optimization Perspective (AISTATS 2021)PDFCode

• Bayesian Pseudocoresets (NeurIPS 2020)PDFCode

• Sparse Variational Inference: Bayesian Coresets from Scratch (NeurIPS 2019)PDFCode

• Bayesian Coreset Construction via Greedy Iterative Geodesic Ascent(ICML 2018)PDFCode

• Training Data Subset Selection for Regression with Controlled Generalization Error(ICML 2021)PDFCode

• Coresets for Near-Convex Functions(NeurIPS 2020)PDF
• On Coresets for Regularized Regression(ICML 2020)PDFCode
• Coresets for Regressions with Panel Data(NeurIPS 2020)PDFCode

• 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