Piotr Indyk

Compact Geometric Representations of Hierarchies COLT 2026 Contradiction Retrieval via Contrastive Learning with Sparsity ICML 2025 Graph-Based Algorithms for Diverse Similarity Search ICML 2025 Improved Algorithms for Kernel Matrix-Vector Multiplication Under Sparsity Assumptions ICLR 2025 Optimal and learned algorithms for the online list update problem with Zipfian accesses ALT 2025 Optimal Algorithms for Augmented Testing of Discrete Distributions NeurIPS 2024 Statistical-Computational Trade-offs for Density Estimation NeurIPS 2024 Addressing Feature Suppression in Unsupervised Visual Representations WACV 2023 Data Structures for Density Estimation ICML 2023 Differentially Private Approximate Near Neighbor Counting in High Dimensions NeurIPS 2023 Near-Linear Time Algorithm for the Chamfer Distance NeurIPS 2023 Subquadratic Algorithms for Kernel Matrices via Kernel Density Estimation ICLR 2023 Worst-case Performance of Popular Approximate Nearest Neighbor Search Implementations: Guarantees and Limitations NeurIPS 2023 Exponentially Improving the Complexity of Simulating the Weisfeiler-Lehman Test with Graph Neural Networks NeurIPS 2022 Faster Linear Algebra for Distance Matrices NeurIPS 2022 Generalization Bounds for Data-Driven Numerical Linear Algebra COLT 2022 Online Page Migration with ML Advice AISTATS 2022 (Optimal) Online Bipartite Matching with Degree Information NeurIPS 2022 Streaming Algorithms for Support-Aware Histograms ICML 2022 Targeted Supervised Contrastive Learning for Long-Tailed Recognition CVPR 2022 Triangle and Four Cycle Counting with Predictions in Graph Streams ICLR 2022 Faster Kernel Matrix Algebra via Density Estimation ICML 2021 Few-Shot Data-Driven Algorithms for Low Rank Approximation NeurIPS 2021 Learning-based Support Estimation in Sublinear Time ICLR 2021 Randomized Dimensionality Reduction for Facility Location and Single-Linkage Clustering ICML 2021 Learning Space Partitions for Nearest Neighbor Search ICLR 2020 Scalable Nearest Neighbor Search for Optimal Transport ICML 2020 Composable Core-sets for Determinant Maximization: A Simple Near-Optimal Algorithm ICML 2019 Estimating Entropy of Distributions in Constant Space NeurIPS 2019 Learning-Based Frequency Estimation Algorithms ICLR 2019 Learning-Based Low-Rank Approximations NeurIPS 2019 Scalable Fair Clustering ICML 2019 Space and Time Efficient Kernel Density Estimation in High Dimensions NeurIPS 2019 Approximate Nearest Neighbors in Limited Space COLT 2018 On the Fine-Grained Complexity of Empirical Risk Minimization: Kernel Methods and Neural Networks NeurIPS 2017 Practical Data-Dependent Metric Compression with Provable Guarantees NeurIPS 2017 A Nearly-Linear Time Framework for Graph-Structured Sparsity IJCAI 2016 Fast recovery from a union of subspaces NeurIPS 2016 A Nearly-Linear Time Framework for Graph-Structured Sparsity ICML 2015 Practical and Optimal LSH for Angular Distance NeurIPS 2015 Learning Approximate Sequential Patterns for Classification JMLR 2009