Piotr Indyk

Publication Activity (10 Years)

Years Active: 1994-2024
Publications (10 Years): 99

Top Venues

CoRR

SODA

NeurIPS

ICML

Publications

Haike Xu, Zongyu Lin, Yizhou Sun, Kai-Wei Chang, Piotr Indyk
SparseCL: Sparse Contrastive Learning for Contradiction Retrieval. CoRR (2024)
Haike Xu, Sandeep Silwal, Piotr Indyk
A Bi-metric Framework for Fast Similarity Search. CoRR (2024)
Justin Y. Chen, Piotr Indyk, David P. Woodruff
Space-Optimal Profile Estimation in Data Streams with Applications to Symmetric Functions. ITCS (2024)
Vaggos Chatziafratis, Piotr Indyk
Dimension-Accuracy Tradeoffs in Contrastive Embeddings for Triplets, Terminals & Top-k Nearest Neighbors. SOSA (2024)
Ainesh Bakshi, Piotr Indyk, Rajesh Jayaram, Sandeep Silwal, Erik Waingarten
Near-Linear Time Algorithm for the Chamfer Distance. NeurIPS (2023)
Alexandr Andoni, Piotr Indyk, Sepideh Mahabadi, Shyam Narayanan
Differentially Private Approximate Near Neighbor Counting in High Dimensions. NeurIPS (2023)
Justin Y. Chen, Piotr Indyk, David P. Woodruff
Space-Optimal Profile Estimation in Data Streams with Applications to Symmetric Functions. CoRR (2023)
Ainesh Bakshi, Piotr Indyk, Rajesh Jayaram, Sandeep Silwal, Erik Waingarten
A Near-Linear Time Algorithm for the Chamfer Distance. CoRR (2023)
Piotr Indyk, Haike Xu
Worst-case Performance of Popular Approximate Nearest Neighbor Search Implementations: Guarantees and Limitations. NeurIPS (2023)
Tianhong Li, Lijie Fan, Yuan Yuan, Hao He, Yonglong Tian, Rogério Feris, Piotr Indyk, Dina Katabi
Addressing Feature Suppression in Unsupervised Visual Representations. WACV (2023)
Nicholas Schiefer, Justin Y. Chen, Piotr Indyk, Shyam Narayanan, Sandeep Silwal, Tal Wagner
Learned Interpolation for Better Streaming Quantile Approximation with Worst-Case Guarantees. CoRR (2023)
Piotr Indyk, Haike Xu
Worst-case Performance of Popular Approximate Nearest Neighbor Search Implementations: Guarantees and Limitations. CoRR (2023)
Vaggos Chatziafratis, Piotr Indyk
Dimension-Accuracy Tradeoffs in Contrastive Embeddings for Triplets, Terminals & Top-k Nearest Neighbors. CoRR (2023)
Yihe Dong, Piotr Indyk, Ilya P. Razenshteyn, Tal Wagner
Learning Space Partitions for Nearest Neighbor Search. IEEE Data Eng. Bull. 46 (3) (2023)
Anders Aamand, Alexandr Andoni, Justin Y. Chen, Piotr Indyk, Shyam Narayanan, Sandeep Silwal
Data Structures for Density Estimation. CoRR (2023)
Nicholas Schiefer, Justin Y. Chen, Piotr Indyk, Shyam Narayanan, Sandeep Silwal, Tal Wagner
Learned Interpolation for Better Streaming Quantile Approximation with Worst-Case Guarantees. ACDA (2023)
Anders Aamand, Alexandr Andoni, Justin Y. Chen, Piotr Indyk, Shyam Narayanan, Sandeep Silwal
Data Structures for Density Estimation. ICML (2023)
Ainesh Bakshi, Piotr Indyk, Praneeth Kacham, Sandeep Silwal, Samson Zhou
Subquadratic Algorithms for Kernel Matrices via Kernel Density Estimation. ICLR (2023)
Justin Y. Chen, Piotr Indyk, Tal Wagner
Streaming Algorithms for Support-Aware Histograms. ICML (2022)
Tianhong Li, Peng Cao, Yuan Yuan, Lijie Fan, Yuzhe Yang, Rogério Feris, Piotr Indyk, Dina Katabi
Targeted Supervised Contrastive Learning for Long-Tailed Recognition. CVPR (2022)
Anders Aamand, Justin Y. Chen, Piotr Indyk, Shyam Narayanan, Ronitt Rubinfeld, Nicholas Schiefer, Sandeep Silwal, Tal Wagner
Exponentially Improving the Complexity of Simulating the Weisfeiler-Lehman Test with Graph Neural Networks. CoRR (2022)
Piotr Indyk, Frederik Mallmann-Trenn, Slobodan Mitrovic, Ronitt Rubinfeld
Online Page Migration with ML Advice. AISTATS (2022)
Justin Y. Chen, Talya Eden, Piotr Indyk, Honghao Lin, Shyam Narayanan, Ronitt Rubinfeld, Sandeep Silwal, Tal Wagner, David P. Woodruff, Michael Zhang
Triangle and Four Cycle Counting with Predictions in Graph Streams. CoRR (2022)
Justin Y. Chen, Talya Eden, Piotr Indyk, Honghao Lin, Shyam Narayanan, Ronitt Rubinfeld, Sandeep Silwal, Tal Wagner, David P. Woodruff, Michael Zhang
Triangle and Four Cycle Counting with Predictions in Graph Streams. ICLR (2022)
Piotr Indyk, Shyam Narayanan, David P. Woodruff
Frequency Estimation with One-Sided Error. SODA (2022)
Piotr Indyk, Sandeep Silwal
Faster Linear Algebra for Distance Matrices. NeurIPS (2022)
Peter L. Bartlett, Piotr Indyk, Tal Wagner
Generalization Bounds for Data-Driven Numerical Linear Algebra. CoRR (2022)
Peter L. Bartlett, Piotr Indyk, Tal Wagner
Generalization Bounds for Data-Driven Numerical Linear Algebra. COLT (2022)
Talya Eden, Piotr Indyk, Haike Xu
Embeddings and Labeling Schemes for A. ITCS (2022)
Piotr Indyk, Tal Wagner
Optimal (Euclidean) Metric Compression. SIAM J. Comput. 51 (3) (2022)
Piotr Indyk, Sandeep Silwal
Faster Linear Algebra for Distance Matrices. CoRR (2022)
Anders Aamand, Justin Y. Chen, Piotr Indyk
(Optimal) Online Bipartite Matching with Degree Information. NeurIPS (2022)
Justin Y. Chen, Piotr Indyk, Tal Wagner
Streaming Algorithms for Support-Aware Histograms. CoRR (2022)
Anders Aamand, Justin Y. Chen, Piotr Indyk, Shyam Narayanan, Ronitt Rubinfeld, Nicholas Schiefer, Sandeep Silwal, Tal Wagner
Exponentially Improving the Complexity of Simulating the Weisfeiler-Lehman Test with Graph Neural Networks. NeurIPS (2022)
Ainesh Bakshi, Piotr Indyk, Praneeth Kacham, Sandeep Silwal, Samson Zhou
Sub-quadratic Algorithms for Kernel Matrices via Kernel Density Estimation. CoRR (2022)
Arturs Backurs, Piotr Indyk, Cameron Musco, Tal Wagner
Faster Kernel Matrix Algebra via Density Estimation. ICML (2021)
Arturs Backurs, Piotr Indyk, Cameron Musco, Tal Wagner
Faster Kernel Matrix Algebra via Density Estimation. CoRR (2021)
Piotr Indyk, Shyam Narayanan, David P. Woodruff
Frequency Estimation with One-Sided Error. CoRR (2021)
Talya Eden, Piotr Indyk, Haike Xu
Embeddings and labeling schemes for A. CoRR (2021)
Shyam Narayanan, Sandeep Silwal, Piotr Indyk, Or Zamir
Randomized Dimensionality Reduction for Facility Location and Single-Linkage Clustering. ICML (2021)
Shyam Narayanan, Sandeep Silwal, Piotr Indyk, Or Zamir
Randomized Dimensionality Reduction for Facility Location and Single-Linkage Clustering. CoRR (2021)
Talya Eden, Piotr Indyk, Shyam Narayanan, Ronitt Rubinfeld, Sandeep Silwal, Tal Wagner
Learning-based Support Estimation in Sublinear Time. CoRR (2021)
Tianhong Li, Peng Cao, Yuan Yuan, Lijie Fan, Yuzhe Yang, Rogério Feris, Piotr Indyk, Dina Katabi
Targeted Supervised Contrastive Learning for Long-Tailed Recognition. CoRR (2021)
Talya Eden, Piotr Indyk, Shyam Narayanan, Ronitt Rubinfeld, Sandeep Silwal, Tal Wagner
Learning-based Support Estimation in Sublinear Time. ICLR (2021)
Piotr Indyk, Tal Wagner, David P. Woodruff
Few-Shot Data-Driven Algorithms for Low Rank Approximation. NeurIPS (2021)
Piotr Indyk, Tal Wagner
Optimal (Euclidean) Metric Compression. CoRR (2021)
Justin Y. Chen, Piotr Indyk
Online Bipartite Matching with Predicted Degrees. CoRR (2021)
Piotr Indyk, Frederik Mallmann-Trenn, Slobodan Mitrovic, Ronitt Rubinfeld
Online Page Migration with ML Advice. CoRR (2020)
Piotr Indyk, Sepideh Mahabadi, Shayan Oveis Gharan, Alireza Rezaei
Composable Core-sets for Determinant Maximization Problems via Spectral Spanners. SODA (2020)
Yihe Dong, Piotr Indyk, Ilya P. Razenshteyn, Tal Wagner
Learning Space Partitions for Nearest Neighbor Search. ICLR (2020)
Arturs Backurs, Yihe Dong, Piotr Indyk, Ilya P. Razenshteyn, Tal Wagner
Scalable Nearest Neighbor Search for Optimal Transport. ICML (2020)
Chen-Yu Hsu, Piotr Indyk, Dina Katabi, Ali Vakilian
Learning-Based Frequency Estimation Algorithms. ICLR (Poster) (2019)
Arturs Backurs, Piotr Indyk, Krzysztof Onak, Baruch Schieber, Ali Vakilian, Tal Wagner
Scalable Fair Clustering. CoRR (2019)
Arturs Backurs, Piotr Indyk, Krzysztof Onak, Baruch Schieber, Ali Vakilian, Tal Wagner
Scalable Fair Clustering. ICML (2019)
Anastasios Sidiropoulos, Mihai Badoiu, Kedar Dhamdhere, Anupam Gupta, Piotr Indyk, Yuri Rabinovich, Harald Räcke, R. Ravi
Approximation Algorithms for Low-Distortion Embeddings into Low-Dimensional Spaces. SIAM J. Discret. Math. 33 (1) (2019)
Piotr Indyk, Sepideh Mahabadi, Ronitt Rubinfeld, Ali Vakilian, Anak Yodpinyanee
Set Cover in Sub-linear Time. CoRR (2019)
Piotr Indyk, Ali Vakilian
Tight Trade-offs for the Maximum k-Coverage Problem in the General Streaming Model. PODS (2019)
Piotr Indyk, Sepideh Mahabadi, Shayan Oveis Gharan, Alireza Rezaei
Composable Core-sets for Determinant Maximization: A Simple Near-Optimal Algorithm. CoRR (2019)
Jayadev Acharya, Sourbh Bhadane, Piotr Indyk, Ziteng Sun
Estimating Entropy of Distributions in Constant Space. CoRR (2019)
Piotr Indyk, Ali Vakilian, Tal Wagner, David P. Woodruff
Sample-Optimal Low-Rank Approximation of Distance Matrices. COLT (2019)
Yihe Dong, Piotr Indyk, Ilya P. Razenshteyn, Tal Wagner
Learning Sublinear-Time Indexing for Nearest Neighbor Search. CoRR (2019)
Piotr Indyk, Ali Vakilian, Yang Yuan
Learning-Based Low-Rank Approximations. NeurIPS (2019)
Arturs Backurs, Piotr Indyk, Tal Wagner
Space and Time Efficient Kernel Density Estimation in High Dimensions. NeurIPS (2019)
Anders Aamand, Piotr Indyk, Ali Vakilian
(Learned) Frequency Estimation Algorithms under Zipfian Distribution. CoRR (2019)
Jayadev Acharya, Sourbh Bhadane, Piotr Indyk, Ziteng Sun
Estimating Entropy of Distributions in Constant Space. NeurIPS (2019)
Piotr Indyk, Ali Vakilian, Tal Wagner, David P. Woodruff
Sample-Optimal Low-Rank Approximation of Distance Matrices. CoRR (2019)
Yihe Dong, Piotr Indyk, Ilya P. Razenshteyn, Tal Wagner
Scalable Nearest Neighbor Search for Optimal Transport. CoRR (2019)
Piotr Indyk, Ali Vakilian, Yang Yuan
Learning-Based Low-Rank Approximations. CoRR (2019)
Sepideh Mahabadi, Piotr Indyk, Shayan Oveis Gharan, Alireza Rezaei
Composable Core-sets for Determinant Maximization: A Simple Near-Optimal Algorithm. ICML (2019)
Haitham Hassanieh, Omid Abari, Michael Rodriguez, Mohammed A. Abdelghany, Dina Katabi, Piotr Indyk
Fast millimeter wave beam alignment. SIGCOMM (2018)
Piotr Indyk, Sepideh Mahabadi, Shayan Oveis Gharan, Alireza Rezaei
Composable Core-sets for Determinant Maximization Problems via Spectral Spanners. CoRR (2018)
Piotr Indyk, Tal Wagner
Approximate Nearest Neighbors in Limited Space. COLT (2018)
Arturs Backurs, Moses Charikar, Piotr Indyk, Paris Siminelakis
Efficient Density Evaluation for Smooth Kernels. FOCS (2018)
Arturs Backurs, Piotr Indyk
Edit Distance Cannot Be Computed in Strongly Subquadratic Time (Unless SETH is False). SIAM J. Comput. 47 (3) (2018)
Alexandr Andoni, Piotr Indyk, Ilya P. Razenshteyn
Approximate Nearest Neighbor Search in High Dimensions. CoRR (2018)
Piotr Indyk, Tal Wagner
Approximate Nearest Neighbors in Limited Space. CoRR (2018)
Sariel Har-Peled, Piotr Indyk, Sepideh Mahabadi
Approximate Sparse Linear Regression. ICALP (2018)
Piotr Indyk, Sepideh Mahabadi, Ronitt Rubinfeld, Ali Vakilian, Anak Yodpinyanee
Set Cover in Sub-linear Time. SODA (2018)
Arturs Backurs, Piotr Indyk, Ludwig Schmidt
On the Fine-Grained Complexity of Empirical Risk Minimization: Kernel Methods and Neural Networks. CoRR (2017)
Arturs Backurs, Piotr Indyk, Ludwig Schmidt
On the Fine-Grained Complexity of Empirical Risk Minimization: Kernel Methods and Neural Networks. NIPS (2017)
Piotr Indyk
Beyond P vs. NP: Quadratic-Time Hardness for Big Data Problems. SPAA (2017)
Piotr Indyk, Ilya P. Razenshteyn, Tal Wagner
Practical Data-Dependent Metric Compression with Provable Guarantees. NIPS (2017)
Piotr Indyk, Tal Wagner
Near-Optimal (Euclidean) Metric Compression. SODA (2017)
Mahdi Cheraghchi, Piotr Indyk
Nearly Optimal Deterministic Algorithm for Sparse Walsh-Hadamard Transform. ACM Trans. Algorithms 13 (3) (2017)
Arturs Backurs, Piotr Indyk, Ludwig Schmidt
Better Approximations for Tree Sparsity in Nearly-Linear Time. SODA (2017)
Haitham Hassanieh, Omid Abari, Michael Rodreguez, Mohammed A. Abdelghany, Dina Katabi, Piotr Indyk
Agile Millimeter Wave Networks with Provable Guarantees. CoRR (2017)
Piotr Indyk, Sepideh Mahabadi, Ronitt Rubinfeld, Jonathan R. Ullman, Ali Vakilian, Anak Yodpinyanee
Fractional Set Cover in the Streaming Model. APPROX-RANDOM (2017)
Piotr Indyk, Ilya P. Razenshteyn, Tal Wagner
Practical Data-Dependent Metric Compression with Provable Guarantees. CoRR (2017)
Chinmay Hegde, Piotr Indyk, Ludwig Schmidt
Fast recovery from a union of subspaces. NIPS (2016)
Piotr Indyk, Tal Wagner
Near-Optimal (Euclidean) Metric Compression. CoRR (2016)
Piotr Indyk, Robert D. Kleinberg, Sepideh Mahabadi, Yang Yuan
Simultaneous Nearest Neighbor Search. SoCG (2016)
Mahdi Cheraghchi, Piotr Indyk
Nearly Optimal Deterministic Algorithm for Sparse Walsh-Hadamard Transform. SODA (2016)
Sariel Har-Peled, Piotr Indyk, Sepideh Mahabadi, Ali Vakilian
Towards Tight Bounds for the Streaming Set Cover Problem. PODS (2016)
Piotr Indyk, Anca Muscholl, Fabian Kuhn
ICALP 2017 - Call for Papers. Bull. EATCS 120 (2016)
Arturs Backurs, Piotr Indyk
Which Regular Expression Patterns Are Hard to Match? FOCS (2016)
Arturs Backurs, Piotr Indyk, Ilya P. Razenshteyn, David P. Woodruff
-median sketching. SODA (2016)
Chinmay Hegde, Piotr Indyk, Ludwig Schmidt
A Nearly-Linear Time Framework for Graph-Structured Sparsity. IJCAI (2016)
Sariel Har-Peled, Piotr Indyk, Sepideh Mahabadi
Approximate Sparse Linear Regression. CoRR (2016)
Piotr Indyk, Robert D. Kleinberg, Sepideh Mahabadi, Yang Yuan
Simultaneous Nearest Neighbor Search. CoRR (2016)
Arturs Backurs, Piotr Indyk
Which Regular Expression Patterns are Hard to Match? CoRR (2015)

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Publication Activity (10 Years)

Top Topics

Top Venues

Piotr Indyk