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ORCIDEric Price 0001
Eric C. Price
Person information
- affiliation: University of Texas at Austin, Department of Computer Science, TX, USA
- affiliation (former): Massachusetts Institute of Technology, Cambridge, MA, USA
- affiliation (former): IBM Almaden Research Center, San Jose, CA, USA
Other persons with the same name
- Eric Price 0002
![[0000-0002-3480-8054]](https://dblp.org/img/orcid-mark.12x12.png "0000-0002-3480-8054")
— Max Planck Institute for Intelligent Systems, Tübingen, Germany (and 1 more)
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2020 – today
- 2024
[c70]Shivam Gupta, Samuel Hopkins, Eric C. Price:
Beyond Catoni: Sharper Rates for Heavy-Tailed and Robust Mean Estimation. COLT 2024: 2232-2269- [c69]Eric Price, Zhiyang Xun:
Spectral Guarantees for Adversarial Streaming PCA. FOCS 2024: 1768-1785 - [c68]Lucas Gretta, Eric Price:
Sharp Noisy Binary Search with Monotonic Probabilities. ICALP 2024: 75:1-75:19 - [c67]Shivam Gupta, Ajil Jalal, Aditya Parulekar, Eric Price, Zhiyang Xun:
Diffusion Posterior Sampling is Computationally Intractable. ICML 2024 - [i63]Shivam Gupta, Ajil Jalal, Aditya Parulekar, Eric Price, Zhiyang Xun:
Diffusion Posterior Sampling is Computationally Intractable. CoRR abs/2402.12727 (2024) - [i62]Eric Price, Zhiyang Xun:
Spectral Guarantees for Adversarial Streaming PCA. CoRR abs/2408.10332 (2024) - 2023
- [j4]Arnab Bhattacharyya, Sutanu Gayen, Eric Price, Vincent Y. F. Tan, N. V. Vinodchandran:
Near-Optimal Learning of Tree-Structured Distributions by Chow and Liu. SIAM J. Comput. 52(3): 761-793 (2023) - [c66]Shivam Gupta, Jasper C. H. Lee, Eric Price:
Finite-Sample Symmetric Mean Estimation with Fisher Information Rate. COLT 2023: 4777-4830 - [c65]Shivam Gupta, Jasper C. H. Lee, Eric Price:
High-dimensional Location Estimation via Norm Concentration for Subgamma Vectors. ICML 2023: 12132-12164 - [c64]Shivam Gupta, Jasper C. H. Lee, Eric Price, Paul Valiant:
Minimax-Optimal Location Estimation. NeurIPS 2023 - [c63]Ajil Jalal, Justin Singh Kang, Ananya Uppal, Kannan Ramchandran, Eric Price:
Learning a 1-layer conditional generative model in total variation. NeurIPS 2023 - [c62]Yihan Zhou, Eric Price:
A Competitive Algorithm for Agnostic Active Learning. NeurIPS 2023 - [c61]Lucas Gretta, Eric Price:
An Improved Online Reduction from PAC Learning to Mistake-Bounded Learning. SOSA 2023: 373-380 - [i61]Shivam Gupta, Jasper C. H. Lee, Eric Price:
High-dimensional Location Estimation via Norm Concentration for Subgamma Vectors. CoRR abs/2302.02497 (2023) - [i60]Shivam Gupta, Jasper C. H. Lee, Eric Price:
Finite-Sample Symmetric Mean Estimation with Fisher Information Rate. CoRR abs/2306.16573 (2023) - [i59]Eric Price, Yihan Zhou:
A Competitive Algorithm for Agnostic Active Learning. CoRR abs/2310.18786 (2023) - [i58]Lucas Gretta, Eric Price:
Sharp Noisy Binary Search with Monotonic Probabilities. CoRR abs/2311.00840 (2023) - [i57]Shivam Gupta, Aditya Parulekar, Eric Price, Zhiyang Xun:
Sample-Efficient Training for Diffusion. CoRR abs/2311.13745 (2023) - 2022
- [c60]Alaa Maalouf, Murad Tukan, Eric Price, Daniel M. Kane, Dan Feldman:
Coresets for Data Discretization and Sine Wave Fitting. AISTATS 2022: 10622-10639 - [c59]Shivam Gupta, Eric Price:
Sharp Constants in Uniformity Testing via the Huber Statistic. COLT 2022: 3113-3192 - [c58]Ashish Chiplunkar, John Kallaugher, Michael Kapralov, Eric Price:
Factorial Lower Bounds for (Almost) Random Order Streams. FOCS 2022: 486-497 - [c57]Eric Price, Sandeep Silwal, Samson Zhou:
Hardness and Algorithms for Robust and Sparse Optimization. ICML 2022: 17926-17944 - [c56]Shuo Yang, Tongzheng Ren, Sanjay Shakkottai, Eric Price, Inderjit S. Dhillon, Sujay Sanghavi:
Linear Bandit Algorithms with Sublinear Time Complexity. ICML 2022: 25241-25260 - [c55]Shivam Gupta, Jasper C. H. Lee, Eric Price, Paul Valiant:
Finite-Sample Maximum Likelihood Estimation of Location. NeurIPS 2022 - [c54]John Kallaugher, Michael Kapralov, Eric Price:
Simulating Random Walks in Random Streams. SODA 2022: 3091-3126 - [i56]Alaa Maalouf, Murad Tukan, Eric Price, Daniel Kane, Dan Feldman:
Coresets for Data Discretization and Sine Wave Fitting. CoRR abs/2203.03009 (2022) - [i55]Shivam Gupta, Jasper C. H. Lee, Eric Price, Paul Valiant:
Finite-Sample Maximum Likelihood Estimation of Location. CoRR abs/2206.02348 (2022) - [i54]Shivam Gupta, Eric Price:
Sharp Constants in Uniformity Testing via the Huber Statistic. CoRR abs/2206.10722 (2022) - [i53]Eric Price, Sandeep Silwal, Samson Zhou:
Hardness and Algorithms for Robust and Sparse Optimization. CoRR abs/2206.14354 (2022) - 2021
- [c53]Aditya Parulekar, Advait Parulekar, Eric Price:
L1 Regression with Lewis Weights Subsampling. APPROX-RANDOM 2021: 49:1-49:21 - [c52]Akshay Kamath, Eric Price, David P. Woodruff:
A Simple Proof of a New Set Disjointness with Applications to Data Streams. CCC 2021: 37:1-37:24 - [c51]Ajil Jalal, Sushrut Karmalkar, Alex Dimakis, Eric Price:
Instance-Optimal Compressed Sensing via Posterior Sampling. ICML 2021: 4709-4720 - [c50]Ajil Jalal, Sushrut Karmalkar, Jessica Hoffmann, Alex Dimakis, Eric Price:
Fairness for Image Generation with Uncertain Sensitive Attributes. ICML 2021: 4721-4732 - [c49]Ajil Jalal, Marius Arvinte, Giannis Daras, Eric Price, Alexandros G. Dimakis, Jonathan I. Tamir:
Robust Compressed Sensing MRI with Deep Generative Priors. NeurIPS 2021: 14938-14954 - [c48]Arnab Bhattacharyya, Sutanu Gayen, Eric Price, N. V. Vinodchandran:
Near-optimal learning of tree-structured distributions by Chow-Liu. STOC 2021: 147-160 - [c47]Ilias Diakonikolas, Themis Gouleakis, Daniel M. Kane, John Peebles, Eric Price:
Optimal testing of discrete distributions with high probability. STOC 2021: 542-555 - [i52]Shuo Yang, Tongzheng Ren, Sanjay Shakkottai, Eric Price, Inderjit S. Dhillon, Sujay Sanghavi:
Linear Bandit Algorithms with Sublinear Time Complexity. CoRR abs/2103.02729 (2021) - [i51]Aditya Parulekar, Advait Parulekar, Eric Price:
L1 Regression with Lewis Weights Subsampling. CoRR abs/2105.09433 (2021) - [i50]Akshay Kamath, Eric Price, David P. Woodruff:
A Simple Proof of a New Set Disjointness with Applications to Data Streams. CoRR abs/2105.11338 (2021) - [i49]Eric Price, Jonathan Scarlett, Nelvin Tan:
Fast Splitting Algorithms for Sparsity-Constrained and Noisy Group Testing. CoRR abs/2106.00308 (2021) - [i48]Ajil Jalal, Sushrut Karmalkar, Alexandros G. Dimakis, Eric Price:
Instance-Optimal Compressed Sensing via Posterior Sampling. CoRR abs/2106.11438 (2021) - [i47]Ajil Jalal, Sushrut Karmalkar, Jessica Hoffmann, Alexandros G. Dimakis, Eric Price:
Fairness for Image Generation with Uncertain Sensitive Attributes. CoRR abs/2106.12182 (2021) - [i46]Ajil Jalal, Marius Arvinte, Giannis Daras, Eric Price, Alexandros G. Dimakis, Jonathan I. Tamir:
Robust Compressed Sensing MRI with Deep Generative Priors. CoRR abs/2108.01368 (2021) - [i45]Ashish Chiplunkar, John Kallaugher, Michael Kapralov, Eric Price:
Approximating Local Graph Structure in Almost Random Order Streams. CoRR abs/2110.10091 (2021) - [i44]John Kallaugher, Michael Kapralov, Eric Price:
Simulating Random Walks in Random Streams. CoRR abs/2112.07532 (2021) - 2020
- [c46]Eric Price, Jonathan Scarlett:
A Fast Binary Splitting Approach to Non-Adaptive Group Testing. APPROX-RANDOM 2020: 13:1-13:20 - [c45]Akshay Kamath, Eric Price, Sushrut Karmalkar:
On the Power of Compressed Sensing with Generative Models. ICML 2020: 5101-5109 - [c44]John Kallaugher, Eric Price:
Separations and equivalences between turnstile streaming and linear sketching. STOC 2020: 1223-1236 - [p1]Eric Price:
Sparse Recovery. Beyond the Worst-Case Analysis of Algorithms 2020: 140-164 - [i43]Eric Price, Jonathan Scarlett:
A Fast Binary Splitting Approach to Non-Adaptive Group Testing. CoRR abs/2006.10268 (2020) - [i42]Ilias Diakonikolas, Themis Gouleakis, Daniel M. Kane, John Peebles, Eric Price:
Optimal Testing of Discrete Distributions with High Probability. CoRR abs/2009.06540 (2020) - [i41]Arnab Bhattacharyya, Sutanu Gayen, Eric Price, N. V. Vinodchandran:
Near-Optimal Learning of Tree-Structured Distributions by Chow-Liu. CoRR abs/2011.04144 (2020) - [i40]Ilias Diakonikolas, Themis Gouleakis, Daniel Kane, John Peebles, Eric Price:
Optimal Testing of Discrete Distributions with High Probability. Electron. Colloquium Comput. Complex. TR20 (2020)
2010 – 2019
- 2019
- [j3]Ilias Diakonikolas, Themis Gouleakis, John Peebles, Eric Price:
Collision-Based Testers are Optimal for Uniformity and Closeness. Chic. J. Theor. Comput. Sci. 2019 (2019) - [c43]Xue Chen, Eric Price:
Active Regression via Linear-Sample Sparsification. COLT 2019: 663-695 - [c42]Xue Chen, Eric Price:
Estimating the Frequency of a Clustered Signal. ICALP 2019: 36:1-36:13 - [c41]Sébastien Bubeck, Yin Tat Lee, Eric Price, Ilya P. Razenshteyn:
Adversarial examples from computational constraints. ICML 2019: 831-840 - [c40]Ilias Diakonikolas, Daniel Kane, Sushrut Karmalkar, Eric Price, Alistair Stewart:
Outlier-Robust High-Dimensional Sparse Estimation via Iterative Filtering. NeurIPS 2019: 10688-10699 - [c39]John Kallaugher, Andrew McGregor, Eric Price, Sofya Vorotnikova:
The Complexity of Counting Cycles in the Adjacency List Streaming Model. PODS 2019: 119-133 - [c38]Sushrut Karmalkar, Eric Price:
Compressed Sensing with Adversarial Sparse Noise via L1 Regression. SOSA 2019: 19:1-19:19 - [c37]Akshay Kamath, Eric Price:
Adaptive Sparse Recovery with Limited Adaptivity. SODA 2019: 2729-2744 - [i39]Xue Chen, Eric Price:
Estimating the Frequency of a Clustered Signal. CoRR abs/1904.13043 (2019) - [i38]John Kallaugher, Eric Price:
Exponential Separations Between Turnstile Streaming and Linear Sketching. CoRR abs/1905.02358 (2019) - [i37]Ilias Diakonikolas, Sushrut Karmalkar, Daniel Kane, Eric Price, Alistair Stewart:
Outlier-Robust High-Dimensional Sparse Estimation via Iterative Filtering. CoRR abs/1911.08085 (2019) - [i36]Akshay Kamath, Sushrut Karmalkar, Eric Price:
Lower Bounds for Compressed Sensing with Generative Models. CoRR abs/1912.02938 (2019) - 2018
- [c36]David Liau, Zhao Song, Eric Price, Ger Yang:
Stochastic Multi-armed Bandits in Constant Space. AISTATS 2018: 386-394 - [c35]John Kallaugher, Michael Kapralov, Eric Price:
The Sketching Complexity of Graph and Hypergraph Counting. FOCS 2018: 556-567 - [c34]Ilias Diakonikolas, Themis Gouleakis, John Peebles, Eric Price:
Sample-Optimal Identity Testing with High Probability. ICALP 2018: 41:1-41:14 - [c33]Ashish Bora, Eric Price, Alexandros G. Dimakis:
AmbientGAN: Generative models from lossy measurements. ICLR 2018 - [i35]Sébastien Bubeck, Eric Price, Ilya P. Razenshteyn:
Adversarial examples from computational constraints. CoRR abs/1805.10204 (2018) - [i34]David Van Veen, Ajil Jalal, Eric Price, Sriram Vishwanath, Alexandros G. Dimakis:
Compressed Sensing with Deep Image Prior and Learned Regularization. CoRR abs/1806.06438 (2018) - [i33]Alexandr Andoni, Lior Kamma, Robert Krauthgamer, Eric Price:
Batch Sparse Recovery, or How to Leverage the Average Sparsity. CoRR abs/1807.08478 (2018) - [i32]John Kallaugher, Michael Kapralov, Eric Price:
The Sketching Complexity of Graph and Hypergraph Counting. CoRR abs/1808.04995 (2018) - [i31]Sushrut Karmalkar, Eric Price:
Compressed Sensing with Adversarial Sparse Noise via L1 Regression. CoRR abs/1809.08055 (2018) - [i30]Sébastien Bubeck, Yin Tat Lee, Eric Price, Ilya P. Razenshteyn:
Adversarial Examples from Cryptographic Pseudo-Random Generators. CoRR abs/1811.06418 (2018) - 2017
- [c32]Cody R. Freitag, Eric Price, William J. Swartworth:
Testing Hereditary Properties of Sequences. APPROX-RANDOM 2017: 44:1-44:10 - [c31]Daniel Kane, Sushrut Karmalkar, Eric Price:
Robust Polynomial Regression up to the Information Theoretic Limit. FOCS 2017: 391-402 - [c30]Eric Price, Zhao Song, David P. Woodruff:
Fast Regression with an $ell_infty$ Guarantee. ICALP 2017: 59:1-59:14 - [c29]Eric Price:
Fast sparse recovery for any RIP-1 matrix. ICASSP 2017: 6379-6383 - [c28]Ashish Bora, Ajil Jalal, Eric Price, Alexandros G. Dimakis:
Compressed Sensing using Generative Models. ICML 2017: 537-546 - [c27]John Kallaugher, Eric Price:
A Hybrid Sampling Scheme for Triangle Counting. SODA 2017: 1778-1797 - [i29]Ashish Bora, Ajil Jalal, Eric Price, Alexandros G. Dimakis:
Compressed Sensing using Generative Models. CoRR abs/1703.03208 (2017) - [i28]Eric Price, Zhao Song, David P. Woodruff:
Fast Regression with an $\ell_\infty$ Guarantee. CoRR abs/1705.10723 (2017) - [i27]Ilias Diakonikolas, Themis Gouleakis, John Peebles, Eric Price:
Sample-Optimal Identity Testing with High Probability. CoRR abs/1708.02728 (2017) - [i26]Daniel M. Kane, Sushrut Karmalkar, Eric Price:
Robust polynomial regression up to the information theoretic limit. CoRR abs/1708.03257 (2017) - [i25]Xue Chen, Eric Price:
Condition number-free query and active learning of linear families. CoRR abs/1711.10051 (2017) - [i24]David Liau, Eric Price, Zhao Song, Ger Yang:
Stochastic Multi-armed Bandits in Constant Space. CoRR abs/1712.09007 (2017) - [i23]Ilias Diakonikolas, Themis Gouleakis, John Peebles, Eric Price:
Sample-Optimal Identity Testing with High Probability. Electron. Colloquium Comput. Complex. TR17 (2017) - 2016
- [c26]Xue Chen, Daniel M. Kane, Eric Price, Zhao Song:
Fourier-Sparse Interpolation without a Frequency Gap. FOCS 2016: 741-750 - [c25]Moritz Hardt, Eric Price, Nati Srebro:
Equality of Opportunity in Supervised Learning. NIPS 2016: 3315-3323 - [r1]Eric Price:
Sparse Fourier Transform. Encyclopedia of Algorithms 2016: 2036-2041 - [i22]Eric Price, Zhao Song:
A Robust Sparse Fourier Transform in the Continuous Setting. CoRR abs/1609.00896 (2016) - [i21]Xue Chen, Daniel M. Kane, Eric Price, Zhao Song:
Fourier-sparse interpolation without a frequency gap. CoRR abs/1609.01361 (2016) - [i20]John Kallaugher, Eric Price:
Improved graph sampling for triangle counting. CoRR abs/1610.02066 (2016) - [i19]Moritz Hardt, Eric Price, Nathan Srebro:
Equality of Opportunity in Supervised Learning. CoRR abs/1610.02413 (2016) - [i18]Eric Price, Wojciech Zaremba, Ilya Sutskever:
Extensions and Limitations of the Neural GPU. CoRR abs/1611.00736 (2016) - [i17]Ilias Diakonikolas, Themis Gouleakis, John Peebles, Eric Price:
Collision-based Testers are Optimal for Uniformity and Closeness. CoRR abs/1611.03579 (2016) - [i16]Ilias Diakonikolas, Themis Gouleakis, John Peebles, Eric Price:
Collision-based Testers are Optimal for Uniformity and Closeness. Electron. Colloquium Comput. Complex. TR16 (2016) - 2015
- [c24]Patrick MacAlpine, Eric Price, Peter Stone:
SCRAM: Scalable Collision-avoiding Role Assignment with Minimal-Makespan for Formational Positioning. AAAI 2015: 2096-2102 - [c23]Eric Price, Zhao Song:
A Robust Sparse Fourier Transform in the Continuous Setting. FOCS 2015: 583-600 - [c22]Xinyang Yi, Constantine Caramanis, Eric Price:
Binary Embedding: Fundamental Limits and Fast Algorithm. ICML 2015: 2162-2170 - [c21]Moritz Hardt, Eric Price:
Tight Bounds for Learning a Mixture of Two Gaussians. STOC 2015: 753-760 - [i15]Xinyang Yi, Constantine Caramanis, Eric Price:
Binary Embedding: Fundamental Limits and Fast Algorithm. CoRR abs/1502.05746 (2015) - [i14]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) - 2014
- [c20]Patrick MacAlpine, Eric Price, Peter Stone:
SCRAM: scalable collision-avoiding role assignment with minimal-makespan for formational positioning. AAMAS 2014: 1463-1464 - [c19]Andrew McGregor, Eric Price, Sofya Vorotnikova:
Trace Reconstruction Revisited. ESA 2014: 689-700 - [c18]Moritz Hardt, Eric Price:
The Noisy Power Method: A Meta Algorithm with Applications. NIPS 2014: 2861-2869 - [c17]Piotr Indyk, Michael Kapralov, Eric Price:
(Nearly) Sample-Optimal Sparse Fourier Transform. SODA 2014: 480-499 - [c16]Gregory T. Minton, Eric Price:
Improved Concentration Bounds for Count-Sketch. SODA 2014: 669-686 - [c15]Jelani Nelson, Eric Price, Mary Wootters:
New constructions of RIP matrices with fast multiplication and fewer rows. SODA 2014: 1515-1528 - [i13]Moritz Hardt, Eric Price:
Sharp bounds for learning a mixture of two gaussians. CoRR abs/1404.4997 (2014) - [i12]Eric Price:
Optimal Lower Bound for Itemset Frequency Indicator Sketches. CoRR abs/1410.2640 (2014) - 2013
- [b1]Eric C. Price:
Sparse recovery and Fourier sampling. Massachusetts Institute of Technology, Cambridge, MA, USA, 2013 - [c14]Badih Ghazi, Haitham Hassanieh, Piotr Indyk, Dina Katabi, Eric Price, Lixin Shi:
Sample-optimal average-case sparse Fourier Transform in two dimensions. Allerton 2013: 1258-1265 - [c13]Eric Price, David P. Woodruff:
Lower Bounds for Adaptive Sparse Recovery. SODA 2013: 652-663 - [i11]Badih Ghazi, Haitham Hassanieh, Piotr Indyk, Dina Katabi, Eric Price, Lixin Shi:
Sample-Optimal Average-Case Sparse Fourier Transform in Two Dimensions. CoRR abs/1303.1209 (2013) - 2012
- [j2]Rishi Gupta, Piotr Indyk, Eric Price, Yaron Rachlin:
Compressive Sensing with Local Geometric Features. Int. J. Comput. Geom. Appl. 22(4): 365- (2012) - [c12]Eric Price, David P. Woodruff:
Applications of the Shannon-Hartley theorem to data streams and sparse recovery. ISIT 2012: 2446-2450 - [c11]Haitham Hassanieh, Piotr Indyk, Dina Katabi, Eric Price:
Simple and practical algorithm for sparse Fourier transform. SODA 2012: 1183-1194 - [c10]Haitham Hassanieh, Piotr Indyk, Dina Katabi, Eric Price:
Nearly optimal sparse fourier transform. STOC 2012: 563-578 - [i10]Haitham Hassanieh, Piotr Indyk, Dina Katabi, Eric Price:
Nearly Optimal Sparse Fourier Transform. CoRR abs/1201.2501 (2012) - [i9]Eric Price, David P. Woodruff:
Lower Bounds for Adaptive Sparse Recovery. CoRR abs/1205.3518 (2012) - [i8]Gregory T. Minton, Eric Price:
Improved Concentration Bounds for Count-Sketch. CoRR abs/1207.5200 (2012) - [i7]Rishi Gupta, Piotr Indyk, Eric Price, Yaron Rachlin:
Compressive Sensing with Local Geometric Features. CoRR abs/1208.2447 (2012) - [i6]Jelani Nelson, Eric Price, Mary Wootters:
New constructions of RIP matrices with fast multiplication and fewer rows. CoRR abs/1211.0986 (2012) - 2011
- [c9]Rishi Gupta, Piotr Indyk, Eric Price, Yaron Rachlin:
Compressive sensing with local geometric features. SCG 2011: 87-96 - [c8]Piotr Indyk, Eric Price, David P. Woodruff:
On the Power of Adaptivity in Sparse Recovery. FOCS 2011: 285-294 - [c7]Eric Price, David P. Woodruff:
(1 + eps)-Approximate Sparse Recovery. FOCS 2011: 295-304 - [c6]Eric Price:
Efficient Sketches for the Set Query Problem. SODA 2011: 41-56 - [c5]Piotr Indyk, Eric Price:
K-median clustering, model-based compressive sensing, and sparse recovery for earth mover distance. STOC 2011: 627-636 - [i5]