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ORCIDPiotr Indyk
Person information
- affiliation: Massachusetts Institute of Technology, Cambridge, MA, USA
- award (2012): Paris Kanellakis Award
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2020 – today
- 2024
[c186]Justin Y. Chen, Piotr Indyk, David P. Woodruff:
Space-Optimal Profile Estimation in Data Streams with Applications to Symmetric Functions. ITCS 2024: 32:1-32:22- [c185]Vaggos Chatziafratis, Piotr Indyk:
Dimension-Accuracy Tradeoffs in Contrastive Embeddings for Triplets, Terminals & Top-k Nearest Neighbors. SOSA 2024: 230-243 - [i68]Haike Xu, Sandeep Silwal, Piotr Indyk:
A Bi-metric Framework for Fast Similarity Search. CoRR abs/2406.02891 (2024) - [i67]Haike Xu, Zongyu Lin, Yizhou Sun, Kai-Wei Chang, Piotr Indyk:
SparseCL: Sparse Contrastive Learning for Contradiction Retrieval. CoRR abs/2406.10746 (2024) - 2023
- [j39]Yihe Dong, Piotr Indyk, Ilya P. Razenshteyn, Tal Wagner:
Learning Space Partitions for Nearest Neighbor Search. IEEE Data Eng. Bull. 46(3): 55-68 (2023) - [c184]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: 87-97 - [c183]Ainesh Bakshi, Piotr Indyk, Praneeth Kacham, Sandeep Silwal, Samson Zhou:
Subquadratic Algorithms for Kernel Matrices via Kernel Density Estimation. ICLR 2023 - [c182]Anders Aamand, Alexandr Andoni, Justin Y. Chen, Piotr Indyk, Shyam Narayanan, Sandeep Silwal:
Data Structures for Density Estimation. ICML 2023: 1-18 - [c181]Alexandr Andoni, Piotr Indyk, Sepideh Mahabadi, Shyam Narayanan:
Differentially Private Approximate Near Neighbor Counting in High Dimensions. NeurIPS 2023 - [c180]Ainesh Bakshi, Piotr Indyk, Rajesh Jayaram, Sandeep Silwal, Erik Waingarten:
Near-Linear Time Algorithm for the Chamfer Distance. NeurIPS 2023 - [c179]Piotr Indyk, Haike Xu:
Worst-case Performance of Popular Approximate Nearest Neighbor Search Implementations: Guarantees and Limitations. NeurIPS 2023 - [c178]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: 1411-1420 - [i66]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 abs/2304.07652 (2023) - [i65]Anders Aamand, Alexandr Andoni, Justin Y. Chen, Piotr Indyk, Shyam Narayanan, Sandeep Silwal:
Data Structures for Density Estimation. CoRR abs/2306.11312 (2023) - [i64]Ainesh Bakshi, Piotr Indyk, Rajesh Jayaram, Sandeep Silwal, Erik Waingarten:
A Near-Linear Time Algorithm for the Chamfer Distance. CoRR abs/2307.03043 (2023) - [i63]Piotr Indyk, Haike Xu:
Worst-case Performance of Popular Approximate Nearest Neighbor Search Implementations: Guarantees and Limitations. CoRR abs/2310.19126 (2023) - [i62]Justin Y. Chen, Piotr Indyk, David P. Woodruff:
Space-Optimal Profile Estimation in Data Streams with Applications to Symmetric Functions. CoRR abs/2311.17868 (2023) - [i61]Vaggos Chatziafratis, Piotr Indyk:
Dimension-Accuracy Tradeoffs in Contrastive Embeddings for Triplets, Terminals & Top-k Nearest Neighbors. CoRR abs/2312.13490 (2023) - 2022
- [j38]Piotr Indyk, Tal Wagner:
Optimal (Euclidean) Metric Compression. SIAM J. Comput. 51(3): 467-491 (2022) - [c177]Piotr Indyk, Frederik Mallmann-Trenn, Slobodan Mitrovic, Ronitt Rubinfeld:
Online Page Migration with ML Advice. AISTATS 2022: 1655-1670 - [c176]Peter L. Bartlett, Piotr Indyk, Tal Wagner:
Generalization Bounds for Data-Driven Numerical Linear Algebra. COLT 2022: 2013-2040 - [c175]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: 6908-6918 - [c174]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 - [c173]Justin Y. Chen, Piotr Indyk, Tal Wagner:
Streaming Algorithms for Support-Aware Histograms. ICML 2022: 3184-3203 - [c172]Talya Eden, Piotr Indyk, Haike Xu:
Embeddings and Labeling Schemes for A. ITCS 2022: 62:1-62:19 - [c171]Anders Aamand, Justin Y. Chen, Piotr Indyk:
(Optimal) Online Bipartite Matching with Degree Information. NeurIPS 2022 - [c170]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 - [c169]Piotr Indyk, Sandeep Silwal:
Faster Linear Algebra for Distance Matrices. NeurIPS 2022 - [c168]Piotr Indyk, Shyam Narayanan, David P. Woodruff:
Frequency Estimation with One-Sided Error. SODA 2022: 695-707 - [i60]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 abs/2203.09572 (2022) - [i59]Peter L. Bartlett, Piotr Indyk, Tal Wagner:
Generalization Bounds for Data-Driven Numerical Linear Algebra. CoRR abs/2206.07886 (2022) - [i58]Justin Y. Chen, Piotr Indyk, Tal Wagner:
Streaming Algorithms for Support-Aware Histograms. CoRR abs/2207.08686 (2022) - [i57]Piotr Indyk, Sandeep Silwal:
Faster Linear Algebra for Distance Matrices. CoRR abs/2210.15114 (2022) - [i56]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 abs/2211.03232 (2022) - [i55]Ainesh Bakshi, Piotr Indyk, Praneeth Kacham, Sandeep Silwal, Samson Zhou:
Sub-quadratic Algorithms for Kernel Matrices via Kernel Density Estimation. CoRR abs/2212.00642 (2022) - 2021
- [c167]Talya Eden, Piotr Indyk, Shyam Narayanan, Ronitt Rubinfeld, Sandeep Silwal, Tal Wagner:
Learning-based Support Estimation in Sublinear Time. ICLR 2021 - [c166]Arturs Backurs, Piotr Indyk, Cameron Musco, Tal Wagner:
Faster Kernel Matrix Algebra via Density Estimation. ICML 2021: 500-510 - [c165]Shyam Narayanan, Sandeep Silwal, Piotr Indyk, Or Zamir:
Randomized Dimensionality Reduction for Facility Location and Single-Linkage Clustering. ICML 2021: 7948-7957 - [c164]Piotr Indyk, Tal Wagner, David P. Woodruff:
Few-Shot Data-Driven Algorithms for Low Rank Approximation. NeurIPS 2021: 10678-10690 - [i54]Arturs Backurs, Piotr Indyk, Cameron Musco, Tal Wagner:
Faster Kernel Matrix Algebra via Density Estimation. CoRR abs/2102.08341 (2021) - [i53]Talya Eden, Piotr Indyk, Shyam Narayanan, Ronitt Rubinfeld, Sandeep Silwal, Tal Wagner:
Learning-based Support Estimation in Sublinear Time. CoRR abs/2106.08396 (2021) - [i52]Shyam Narayanan, Sandeep Silwal, Piotr Indyk, Or Zamir:
Randomized Dimensionality Reduction for Facility Location and Single-Linkage Clustering. CoRR abs/2107.01804 (2021) - [i51]Piotr Indyk, Tal Wagner:
Optimal (Euclidean) Metric Compression. CoRR abs/2110.03152 (2021) - [i50]Justin Y. Chen, Piotr Indyk:
Online Bipartite Matching with Predicted Degrees. CoRR abs/2110.11439 (2021) - [i49]Piotr Indyk, Shyam Narayanan, David P. Woodruff:
Frequency Estimation with One-Sided Error. CoRR abs/2111.03953 (2021) - [i48]Talya Eden, Piotr Indyk, Haike Xu:
Embeddings and labeling schemes for A. CoRR abs/2111.10041 (2021) - [i47]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 abs/2111.13998 (2021) - 2020
- [c163]Yihe Dong, Piotr Indyk, Ilya P. Razenshteyn, Tal Wagner:
Learning Space Partitions for Nearest Neighbor Search. ICLR 2020 - [c162]Arturs Backurs, Yihe Dong, Piotr Indyk, Ilya P. Razenshteyn, Tal Wagner:
Scalable Nearest Neighbor Search for Optimal Transport. ICML 2020: 497-506 - [c161]Piotr Indyk, Sepideh Mahabadi, Shayan Oveis Gharan, Alireza Rezaei:
Composable Core-sets for Determinant Maximization Problems via Spectral Spanners. SODA 2020: 1675-1694 - [i46]Piotr Indyk, Frederik Mallmann-Trenn, Slobodan Mitrovic, Ronitt Rubinfeld:
Online Page Migration with ML Advice. CoRR abs/2006.05028 (2020)
2010 – 2019
- 2019
- [j37]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): 454-473 (2019) - [c160]Piotr Indyk, Ali Vakilian, Tal Wagner, David P. Woodruff:
Sample-Optimal Low-Rank Approximation of Distance Matrices. COLT 2019: 1723-1751 - [c159]Chen-Yu Hsu, Piotr Indyk, Dina Katabi, Ali Vakilian:
Learning-Based Frequency Estimation Algorithms. ICLR (Poster) 2019 - [c158]Arturs Backurs, Piotr Indyk, Krzysztof Onak, Baruch Schieber, Ali Vakilian, Tal Wagner:
Scalable Fair Clustering. ICML 2019: 405-413 - [c157]Sepideh Mahabadi, Piotr Indyk, Shayan Oveis Gharan, Alireza Rezaei:
Composable Core-sets for Determinant Maximization: A Simple Near-Optimal Algorithm. ICML 2019: 4254-4263 - [c156]Jayadev Acharya, Sourbh Bhadane, Piotr Indyk, Ziteng Sun:
Estimating Entropy of Distributions in Constant Space. NeurIPS 2019: 5163-5174 - [c155]Piotr Indyk, Ali Vakilian, Yang Yuan:
Learning-Based Low-Rank Approximations. NeurIPS 2019: 7400-7410 - [c154]Arturs Backurs, Piotr Indyk, Tal Wagner:
Space and Time Efficient Kernel Density Estimation in High Dimensions. NeurIPS 2019: 15773-15782 - [c153]Piotr Indyk, Ali Vakilian:
Tight Trade-offs for the Maximum k-Coverage Problem in the General Streaming Model. PODS 2019: 200-217 - [i45]Yihe Dong, Piotr Indyk, Ilya P. Razenshteyn, Tal Wagner:
Learning Sublinear-Time Indexing for Nearest Neighbor Search. CoRR abs/1901.08544 (2019) - [i44]Arturs Backurs, Piotr Indyk, Krzysztof Onak, Baruch Schieber, Ali Vakilian, Tal Wagner:
Scalable Fair Clustering. CoRR abs/1902.03519 (2019) - [i43]Piotr Indyk, Sepideh Mahabadi, Ronitt Rubinfeld, Ali Vakilian, Anak Yodpinyanee:
Set Cover in Sub-linear Time. CoRR abs/1902.03534 (2019) - [i42]Piotr Indyk, Ali Vakilian, Tal Wagner, David P. Woodruff:
Sample-Optimal Low-Rank Approximation of Distance Matrices. CoRR abs/1906.00339 (2019) - [i41]Piotr Indyk, Sepideh Mahabadi, Shayan Oveis Gharan, Alireza Rezaei:
Composable Core-sets for Determinant Maximization: A Simple Near-Optimal Algorithm. CoRR abs/1907.03197 (2019) - [i40]Anders Aamand, Piotr Indyk, Ali Vakilian:
(Learned) Frequency Estimation Algorithms under Zipfian Distribution. CoRR abs/1908.05198 (2019) - [i39]Yihe Dong, Piotr Indyk, Ilya P. Razenshteyn, Tal Wagner:
Scalable Nearest Neighbor Search for Optimal Transport. CoRR abs/1910.04126 (2019) - [i38]Piotr Indyk, Ali Vakilian, Yang Yuan:
Learning-Based Low-Rank Approximations. CoRR abs/1910.13984 (2019) - [i37]Jayadev Acharya, Sourbh Bhadane, Piotr Indyk, Ziteng Sun:
Estimating Entropy of Distributions in Constant Space. CoRR abs/1911.07976 (2019) - 2018
- [j36]Arturs Backurs, Piotr Indyk:
Edit Distance Cannot Be Computed in Strongly Subquadratic Time (Unless SETH is False). SIAM J. Comput. 47(3): 1087-1097 (2018) - [c152]Piotr Indyk, Tal Wagner:
Approximate Nearest Neighbors in Limited Space. COLT 2018: 2012-2036 - [c151]Arturs Backurs, Moses Charikar, Piotr Indyk, Paris Siminelakis:
Efficient Density Evaluation for Smooth Kernels. FOCS 2018: 615-626 - [c150]Sariel Har-Peled, Piotr Indyk, Sepideh Mahabadi:
Approximate Sparse Linear Regression. ICALP 2018: 77:1-77:14 - [c149]Haitham Hassanieh, Omid Abari, Michael Rodriguez, Mohammed A. Abdelghany, Dina Katabi, Piotr Indyk:
Fast millimeter wave beam alignment. SIGCOMM 2018: 432-445 - [c148]Piotr Indyk, Sepideh Mahabadi, Ronitt Rubinfeld, Ali Vakilian, Anak Yodpinyanee:
Set Cover in Sub-linear Time. SODA 2018: 2467-2486 - [i36]Alexandr Andoni, Piotr Indyk, Ilya P. Razenshteyn:
Approximate Nearest Neighbor Search in High Dimensions. CoRR abs/1806.09823 (2018) - [i35]Piotr Indyk, Tal Wagner:
Approximate Nearest Neighbors in Limited Space. CoRR abs/1807.00112 (2018) - [i34]Piotr Indyk, Sepideh Mahabadi, Shayan Oveis Gharan, Alireza Rezaei:
Composable Core-sets for Determinant Maximization Problems via Spectral Spanners. CoRR abs/1807.11648 (2018) - 2017
- [j35]Mahdi Cheraghchi, Piotr Indyk:
Nearly Optimal Deterministic Algorithm for Sparse Walsh-Hadamard Transform. ACM Trans. Algorithms 13(3): 34:1-34:36 (2017) - [c147]Piotr Indyk, Sepideh Mahabadi, Ronitt Rubinfeld, Jonathan R. Ullman, Ali Vakilian, Anak Yodpinyanee:
Fractional Set Cover in the Streaming Model. APPROX-RANDOM 2017: 12:1-12:20 - [c146]Piotr Indyk, Ilya P. Razenshteyn, Tal Wagner:
Practical Data-Dependent Metric Compression with Provable Guarantees. NIPS 2017: 2617-2626 - [c145]Arturs Backurs, Piotr Indyk, Ludwig Schmidt:
On the Fine-Grained Complexity of Empirical Risk Minimization: Kernel Methods and Neural Networks. NIPS 2017: 4308-4318 - [c144]Piotr Indyk, Tal Wagner:
Near-Optimal (Euclidean) Metric Compression. SODA 2017: 710-723 - [c143]Arturs Backurs, Piotr Indyk, Ludwig Schmidt:
Better Approximations for Tree Sparsity in Nearly-Linear Time. SODA 2017: 2215-2229 - [c142]Piotr Indyk:
Beyond P vs. NP: Quadratic-Time Hardness for Big Data Problems. SPAA 2017: 1 - [e2]Ioannis Chatzigiannakis, Piotr Indyk, Fabian Kuhn, Anca Muscholl:
44th International Colloquium on Automata, Languages, and Programming, ICALP 2017, July 10-14, 2017, Warsaw, Poland. LIPIcs 80, Schloss Dagstuhl - Leibniz-Zentrum für Informatik 2017, ISBN 978-3-95977-041-5 [contents] - [i33]Arturs Backurs, Piotr Indyk, Ludwig Schmidt:
On the Fine-Grained Complexity of Empirical Risk Minimization: Kernel Methods and Neural Networks. CoRR abs/1704.02958 (2017) - [i32]Haitham Hassanieh, Omid Abari, Michael Rodreguez, Mohammed A. Abdelghany, Dina Katabi, Piotr Indyk:
Agile Millimeter Wave Networks with Provable Guarantees. CoRR abs/1706.06935 (2017) - [i31]Piotr Indyk, Ilya P. Razenshteyn, Tal Wagner:
Practical Data-Dependent Metric Compression with Provable Guarantees. CoRR abs/1711.01520 (2017) - 2016
- [j34]Piotr Indyk, Anca Muscholl, Fabian Kuhn:
ICALP 2017 - Call for Papers. Bull. EATCS 120 (2016) - [c141]Piotr Indyk, Robert D. Kleinberg, Sepideh Mahabadi, Yang Yuan:
Simultaneous Nearest Neighbor Search. SoCG 2016: 44:1-44:15 - [c140]Arturs Backurs, Piotr Indyk:
Which Regular Expression Patterns Are Hard to Match? FOCS 2016: 457-466 - [c139]Chinmay Hegde, Piotr Indyk, Ludwig Schmidt:
A Nearly-Linear Time Framework for Graph-Structured Sparsity. IJCAI 2016: 4165-4169 - [c138]Chinmay Hegde, Piotr Indyk, Ludwig Schmidt:
Fast recovery from a union of subspaces. NIPS 2016: 4394-4402 - [c137]Sariel Har-Peled, Piotr Indyk, Sepideh Mahabadi, Ali Vakilian:
Towards Tight Bounds for the Streaming Set Cover Problem. PODS 2016: 371-383 - [c136]Mahdi Cheraghchi, Piotr Indyk:
Nearly Optimal Deterministic Algorithm for Sparse Walsh-Hadamard Transform. SODA 2016: 298-317 - [c135]Arturs Backurs, Piotr Indyk, Ilya P. Razenshteyn, David P. Woodruff:
Nearly-optimal bounds for sparse recovery in generic norms, with applications to k-median sketching. SODA 2016: 318-337 - [p2]Graham Cormode, Piotr Indyk:
Stable Distributions in Streaming Computations. Data Stream Management 2016: 283-300 - [i30]Piotr Indyk, Robert D. Kleinberg, Sepideh Mahabadi, Yang Yuan:
Simultaneous Nearest Neighbor Search. CoRR abs/1604.02188 (2016) - [i29]Piotr Indyk, Tal Wagner:
Near-Optimal (Euclidean) Metric Compression. CoRR abs/1609.06295 (2016) - [i28]Sariel Har-Peled, Piotr Indyk, Sepideh Mahabadi:
Approximate Sparse Linear Regression. CoRR abs/1609.08739 (2016) - 2015
- [j33]Chinmay Hegde, Piotr Indyk, Ludwig Schmidt:
Fast Algorithms for Structured Sparsity. Bull. EATCS 117 (2015) - [j32]Albert Kim, Eric Blais, Aditya G. Parameswaran, Piotr Indyk, Samuel Madden, Ronitt Rubinfeld:
Rapid Sampling for Visualizations with Ordering Guarantees. Proc. VLDB Endow. 8(5): 521-532 (2015) - [j31]Chinmay Hegde, Piotr Indyk, Ludwig Schmidt:
Approximation Algorithms for Model-Based Compressive Sensing. IEEE Trans. Inf. Theory 61(9): 5129-5147 (2015) - [c134]Ludwig Schmidt, Chinmay Hegde, Piotr Indyk, Ligang Lu, Xingang Chi, Detlef Hohl:
Seismic feature extraction using steiner tree methods. ICASSP 2015: 1647-1651 - [c133]Chinmay Hegde, Piotr Indyk, Ludwig Schmidt:
A Nearly-Linear Time Framework for Graph-Structured Sparsity. ICML 2015: 928-937 - [c132]Alexandr Andoni, Piotr Indyk, Thijs Laarhoven, Ilya P. Razenshteyn, Ludwig Schmidt:
Practical and Optimal LSH for Angular Distance. NIPS 2015: 1225-1233 - [c131]Piotr Indyk, Reut Levi, Ronitt Rubinfeld:
Erratum for: Approximating and Testing k-Histogram Distributions in Sub-linear Time. PODS 2015: 343 - [c130]Arturs Backurs, Piotr Indyk:
Edit Distance Cannot Be Computed in Strongly Subquadratic Time (unless SETH is false). STOC 2015: 51-58 - [e1]Piotr Indyk:
Proceedings of the Twenty-Sixth Annual ACM-SIAM Symposium on Discrete Algorithms, SODA 2015, San Diego, CA, USA, January 4-6, 2015. SIAM 2015, ISBN 978-1-61197-374-7 [contents] - [i27]Arturs Backurs, Piotr Indyk, Eric Price, Ilya P. Razenshteyn, David P. Woodruff:
Nearly-optimal bounds for sparse recovery in generic norms, with applications to $k$-median sketching. CoRR abs/1504.01076 (2015) - [i26]Mahdi Cheraghchi, Piotr Indyk:
Nearly Optimal Deterministic Algorithm for Sparse Walsh-Hadamard Transform. CoRR abs/1504.07648 (2015) - [i25]Piotr Indyk, Sepideh Mahabadi, Ali Vakilian:
Towards Tight Bounds for the Streaming Set Cover Problem. CoRR abs/1509.00118 (2015) - [i24]Alexandr Andoni, Piotr Indyk, Thijs Laarhoven, Ilya P. Razenshteyn, Ludwig Schmidt:
Practical and Optimal LSH for Angular Distance. CoRR abs/1509.02897 (2015) - [i23]Arturs Backurs, Piotr Indyk:
Which Regular Expression Patterns are Hard to Match? CoRR abs/1511.07070 (2015) - [i22]Mahdi Cheraghchi, Piotr Indyk:
Nearly Optimal Deterministic Algorithm for Sparse Walsh-Hadamard Transform. Electron. Colloquium Comput. Complex. TR15 (2015) - 2014
- [j30]Anna C. Gilbert, Piotr Indyk, Mark A. Iwen, Ludwig Schmidt:
Recent Developments in the Sparse Fourier Transform: A compressed Fourier transform for big data. IEEE Signal Process. Mag. 31(5): 91-100 (2014) - [c129]Arturs Backurs, Piotr Indyk:
Better embeddings for planar Earth-Mover Distance over sparse sets. SoCG 2014: 280 - [c128]Piotr Indyk, Michael Kapralov:
Sample-Optimal Fourier Sampling in Any Constant Dimension. FOCS 2014: 514-523 - [c127]Chinmay Hegde, Piotr Indyk, Ludwig Schmidt:
Nearly Linear-Time Model-Based Compressive Sensing. ICALP (1) 2014: 588-599 - [c126]Ludwig Schmidt, Chinmay Hegde, Piotr Indyk, Jonathan Kane, Ligang Lu, Detlef Hohl:
Automatic fault localization using the generalized Earth Mover's distance. ICASSP 2014: 8134-8138 - [c125]