default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDJerry Li 0001
Jerry Zheng Li
Person information
- affiliation: University of Washington, WA, USA
- affiliation (former): Microsoft Research AI
- affiliation (former): Massachusetts Institute of Technology (MIT)
Other persons with the same name
- Jerry Li — disambiguation page
- Jerry Li 0002 — Snap Corporation, Seattle, WA, USA
- Jerry Li 0003 — Northwestern University Evanston, IL, USA
- Jerry Li 0004
![[0000-0002-8774-826X]](https://devdomain4test.ir/img/orcid-mark.12x12.png "0000-0002-8774-826X")
— Torrey Pines High School, San Diego, CA, USA
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
showing all ?? records
2020 – today
- 2026
[j5]Clément Canonne, Samuel B. Hopkins, Jerry Zheng Li, Allen Liu, Shyam Narayanan:
The Full Landscape of Robust Mean Testing: Sharp Separations between Oblivious and Adaptive Contamination. SIAM J. Comput. 55(3): S23-192 (2026)- [c76]Ziyun Chen, Jerry Li, Kevin Tian, Yusong Zhu:
Separating Oblivious and Adaptive Models of Variable Selection (Extended Abstract). COLT 2026: 1113-1114 - [c75]Sitan Chen, Kevin Cong, Jerry Li:
Optimal Inference Schedules for Masked Diffusion Models. COLT 2026: 1279-1311 - [c74]Spencer Compton, Jerry Li:
Density estimation for Hellinger via minimum-distance estimators: mixtures of Gaussians, log-concave, and more. COLT 2026: 1436-1475 - [c73]Ziyun Chen, Spencer Compton, Daniel M. Kane, Jerry Li:
High-Accuracy List-Decodable Mean Estimation. STOC 2026: 767-776 - [c72]Jun-Ting Hsieh, Daniel M. Kane, Pravesh K. Kothari, Jerry Li, Sidhanth Mohanty, Stefan Tiegel:
Rigorous Implications of the Low-Degree Heuristic. STOC 2026: 1763-1770 - [c71]Andrea Coladangelo, Jerry Li, Joseph Slote, Ellen Wu:
The Power of Two Bases: Robust and Copy-Optimal Certification of Nearly All Quantum States with Few-Qubit Measurements. STOC 2026: 1771-1776 - [i79]Jun-Ting Hsieh, Daniel M. Kane, Pravesh K. Kothari, Jerry Li, Sidhanth Mohanty, Stefan Tiegel:
Rigorous Implications of the Low-Degree Heuristic. CoRR abs/2601.05850 (2026) - [i78]Ziyun Chen, Jerry Li, Kevin Tian, Yusong Zhu:
Separating Oblivious and Adaptive Models of Variable Selection. CoRR abs/2602.16568 (2026) - [i77]Spencer Compton, Jerry Li:
Density estimation for Hellinger via minimum-distance estimators: mixtures of Gaussians, log-concave, and more. CoRR abs/2606.11469 (2026) - 2025
- [c70]Sitan Chen, Jaume de Dios Pont, Jun-Ting Hsieh, Hsin-Yuan Huang, Jane Lange, Jerry Li:
Predicting quantum channels over general product distributions. COLT 2025: 986-1007 - [c69]Eric Frankel, Sitan Chen, Jerry Li, Pang Wei Koh, Lillian J. Ratliff, Sewoong Oh:
S4S: Solving for a Fast Diffusion Model Solver. ICML 2025 - [c68]Ainesh Bakshi, John Bostanci, William Kretschmer, Zeph Landau, Jerry Li, Allen Liu, Ryan O'Donnell, Ewin Tang:
Learning the Closest Product State. STOC 2025: 1212-1221 - [i76]Eric Frankel, Sitan Chen, Jerry Li, Pang Wei Koh, Lillian J. Ratliff, Sewoong Oh:
S4S: Solving for a Diffusion Model Solver. CoRR abs/2502.17423 (2025) - [i75]Alvan Arulandu, Ilias Diakonikolas, Daniel M. Kane, Jerry Zheng Li:
Agnostic Product Mixed State Tomography via Robust Statistics. CoRR abs/2510.08472 (2025) - [i74]Sitan Chen, Kevin Cong, Jerry Li:
Optimal Inference Schedules for Masked Diffusion Models. CoRR abs/2511.04647 (2025) - [i73]Ziyun Chen, Spencer Compton, Daniel Kane, Jerry Li:
High-Accuracy List-Decodable Mean Estimation. CoRR abs/2511.17822 (2025) - 2024
- [j4]Sinho Chewi, Jaume de Dios Pont, Jerry Li, Chen Lu, Shyam Narayanan:
Query Lower Bounds for Log-concave Sampling. J. ACM 71(4): 29:1-29:42 (2024) - [c67]Arun Jambulapati, Syamantak Kumar, Jerry Li, Shourya Pandey, Ankit Pensia, Kevin Tian:
Black-Box k-to-1-PCA Reductions: Theory and Applications. COLT 2024: 2564-2607 - [c66]Jonathan A. Kelner, Jerry Li, Allen Liu, Aaron Sidford, Kevin Tian:
Semi-Random Matrix Completion via Flow-Based Adaptive Reweighting. NeurIPS 2024 - [c65]Sitan Chen, Jerry Li, Allen Liu:
An Optimal Tradeoff between Entanglement and Copy Complexity for State Tomography. STOC 2024: 1331-1342 - [i72]Sitan Chen, Jerry Li, Allen Liu:
An optimal tradeoff between entanglement and copy complexity for state tomography. CoRR abs/2402.16353 (2024) - [i71]Arun Jambulapati, Syamantak Kumar, Jerry Li, Shourya Pandey, Ankit Pensia, Kevin Tian:
Black-Box k-to-1-PCA Reductions: Theory and Applications. CoRR abs/2403.03905 (2024) - [i70]Sitan Chen, Jerry Li, Allen Liu:
Optimal high-precision shadow estimation. CoRR abs/2407.13874 (2024) - [i69]Sitan Chen, Jaume de Dios Pont, Jun-Ting Hsieh, Hsin-Yuan Huang, Jane Lange, Jerry Li:
Predicting quantum channels over general product distributions. CoRR abs/2409.03684 (2024) - 2023
- [c64]Jonathan A. Kelner, Jerry Li, Allen Liu, Aaron Sidford, Kevin Tian:
Semi-Random Sparse Recovery in Nearly-Linear Time. COLT 2023: 2352-2398 - [c63]Reid Pryzant, Dan Iter, Jerry Li, Yin Tat Lee, Chenguang Zhu, Michael Zeng:
Automatic Prompt Optimization with "Gradient Descent" and Beam Search. EMNLP 2023: 7957-7968 - [c62]Sitan Chen, Brice Huang, Jerry Li, Allen Liu, Mark Sellke:
When Does Adaptivity Help for Quantum State Learning? FOCS 2023: 391-404 - [c61]Jonathan A. Kelner, Jerry Li, Allen Liu, Aaron Sidford, Kevin Tian:
Matrix Completion in Almost-Verification Time. FOCS 2023: 2102-2128 - [c60]Sinho Chewi, Jaume de Dios Pont, Jerry Li, Chen Lu, Shyam Narayanan:
Query lower bounds for log-concave sampling. FOCS 2023: 2139-2148 - [c59]Clément L. Canonne, Samuel B. Hopkins, Jerry Li, Allen Liu, Shyam Narayanan:
The Full Landscape of Robust Mean Testing: Sharp Separations between Oblivious and Adaptive Contamination. FOCS 2023: 2159-2168 - [c58]Sitan Chen, Sinho Chewi, Jerry Li, Yuanzhi Li, Adil Salim, Anru Zhang:
Sampling is as easy as learning the score: theory for diffusion models with minimal data assumptions. ICLR 2023 - [c57]Arun Jambulapati, Jerry Li, Christopher Musco, Kirankumar Shiragur, Aaron Sidford, Kevin Tian:
Structured Semidefinite Programming for Recovering Structured Preconditioners. NeurIPS 2023 - [c56]Sitan Chen, Jerry Li, Yuanzhi Li, Anru R. Zhang:
Learning Polynomial Transformations via Generalized Tensor Decompositions. STOC 2023: 1671-1684 - [i68]Sinho Chewi, Jaume de Dios Pont, Jerry Li, Chen Lu, Shyam Narayanan:
Query lower bounds for log-concave sampling. CoRR abs/2304.02599 (2023) - [i67]Reid Pryzant, Dan Iter, Jerry Li, Yin Tat Lee, Chenguang Zhu, Michael Zeng:
Automatic Prompt Optimization with "Gradient Descent" and Beam Search. CoRR abs/2305.03495 (2023) - [i66]Clément L. Canonne, Samuel B. Hopkins, Jerry Li, Allen Liu, Shyam Narayanan:
The Full Landscape of Robust Mean Testing: Sharp Separations between Oblivious and Adaptive Contamination. CoRR abs/2307.10273 (2023) - [i65]Jonathan A. Kelner, Jerry Li, Allen Liu, Aaron Sidford, Kevin Tian:
Matrix Completion in Almost-Verification Time. CoRR abs/2308.03661 (2023) - [i64]Arun Jambulapati, Jerry Li, Christopher Musco, Kirankumar Shiragur, Aaron Sidford, Kevin Tian:
Structured Semidefinite Programming for Recovering Structured Preconditioners. CoRR abs/2310.18265 (2023) - 2022
- [c55]Clément L. Canonne, Ayush Jain, Gautam Kamath, Jerry Li:
The Price of Tolerance in Distribution Testing. COLT 2022: 573-624 - [c54]Sitan Chen, Jerry Li, Ryan O'Donnell:
Toward Instance-Optimal State Certification With Incoherent Measurements. COLT 2022: 2541-2596 - [c53]Sitan Chen, Jerry Li, Brice Huang, Allen Liu:
Tight Bounds for Quantum State Certification with Incoherent Measurements. FOCS 2022: 1205-1213 - [c52]Sitan Chen, Jerry Li, Yuanzhi Li, Raghu Meka:
Minimax Optimality (Probably) Doesn't Imply Distribution Learning for GANs. ICLR 2022 - [c51]Sitan Chen, Jerry Li, Yuanzhi Li:
Learning (Very) Simple Generative Models Is Hard. NeurIPS 2022 - [c50]Allen Liu, Jerry Li, Ankur Moitra:
Robust Model Selection and Nearly-Proper Learning for GMMs. NeurIPS 2022 - [c49]Allen Liu, Jerry Li:
Clustering mixtures with almost optimal separation in polynomial time. STOC 2022: 1248-1261 - [c48]Ilias Diakonikolas, Daniel M. Kane, Daniel Kongsgaard, Jerry Li, Kevin Tian:
Clustering mixture models in almost-linear time via list-decodable mean estimation. STOC 2022: 1262-1275 - [i63]Sitan Chen, Jerry Li, Yuanzhi Li, Raghu Meka:
Minimax Optimality (Probably) Doesn't Imply Distribution Learning for GANs. CoRR abs/2201.07206 (2022) - [i62]Jonathan A. Kelner, Jerry Li, Allen Liu, Aaron Sidford, Kevin Tian:
Semi-Random Sparse Recovery in Nearly-Linear Time. CoRR abs/2203.04002 (2022) - [i61]Sitan Chen, Jerry Li, Yuanzhi Li, Anru R. Zhang:
Learning Polynomial Transformations. CoRR abs/2204.04209 (2022) - [i60]Sitan Chen, Brice Huang, Jerry Li, Allen Liu:
Tight Bounds for Quantum State Certification with Incoherent Measurements. CoRR abs/2204.07155 (2022) - [i59]Sitan Chen, Jerry Li, Yuanzhi Li:
Learning (Very) Simple Generative Models Is Hard. CoRR abs/2205.16003 (2022) - [i58]Sitan Chen, Brice Huang, Jerry Li, Allen Liu, Mark Sellke:
Tight Bounds for State Tomography with Incoherent Measurements. CoRR abs/2206.05265 (2022) - [i57]Sitan Chen, Sinho Chewi, Jerry Li, Yuanzhi Li, Adil Salim, Anru R. Zhang:
Sampling is as easy as learning the score: theory for diffusion models with minimal data assumptions. CoRR abs/2209.11215 (2022) - [i56]Sitan Chen, Jordan Cotler, Hsin-Yuan Huang, Jerry Li:
The Complexity of NISQ. CoRR abs/2210.07234 (2022) - 2021
- [j3]Ilias Diakonikolas, Gautam Kamath, Daniel M. Kane, Jerry Li, Ankur Moitra, Alistair Stewart:
Robustness meets algorithms. Commun. ACM 64(5): 107-115 (2021) - [c47]Matthew S. Brennan, Guy Bresler, Samuel B. Hopkins, Jerry Li, Tselil Schramm:
Statistical Query Algorithms and Low Degree Tests Are Almost Equivalent. COLT 2021: 774 - [c46]Jasper C. H. Lee, Jerry Li, Christopher Musco, Jeff M. Phillips, Wai Ming Tai:
Finding an Approximate Mode of a Kernel Density Estimate. ESA 2021: 61:1-61:19 - [c45]Sitan Chen, Jordan Cotler, Hsin-Yuan Huang, Jerry Li:
Exponential Separations Between Learning With and Without Quantum Memory. FOCS 2021: 574-585 - [c44]Zeyuan Allen-Zhu, Faeze Ebrahimianghazani, Jerry Li, Dan Alistarh:
Byzantine-Resilient Non-Convex Stochastic Gradient Descent. ICLR 2021 - [c43]Dan Hendrycks, Collin Burns, Steven Basart, Andrew Critch, Jerry Li, Dawn Song, Jacob Steinhardt:
Aligning AI With Shared Human Values. ICLR 2021 - [c42]Arun Jambulapati, Jerry Li, Tselil Schramm, Kevin Tian:
Robust Regression Revisited: Acceleration and Improved Estimation Rates. NeurIPS 2021: 4475-4488 - [c41]Ilias Diakonikolas, Daniel Kane, Daniel Kongsgaard, Jerry Li, Kevin Tian:
List-Decodable Mean Estimation in Nearly-PCA Time. NeurIPS 2021: 10195-10208 - [i55]Sitan Chen, Jerry Li, Ryan O'Donnell:
Toward Instance-Optimal State Certification With Incoherent Measurements. CoRR abs/2102.13098 (2021) - [i54]Jerry Li, Allen Liu, Ankur Moitra:
Sparsification for Sums of Exponentials and its Algorithmic Applications. CoRR abs/2106.02774 (2021) - [i53]Ilias Diakonikolas, Daniel M. Kane, Daniel Kongsgaard, Jerry Li, Kevin Tian:
Clustering Mixture Models in Almost-Linear Time via List-Decodable Mean Estimation. CoRR abs/2106.08537 (2021) - [i52]Arun Jambulapati, Jerry Li, Tselil Schramm, Kevin Tian:
Robust Regression Revisited: Acceleration and Improved Estimation Rates. CoRR abs/2106.11938 (2021) - [i51]Clément L. Canonne, Ayush Jain, Gautam Kamath, Jerry Li:
The Price of Tolerance in Distribution Testing. CoRR abs/2106.13414 (2021) - [i50]Sitan Chen, Jordan Cotler, Hsin-Yuan Huang, Jerry Li:
A Hierarchy for Replica Quantum Advantage. CoRR abs/2111.05874 (2021) - [i49]Sitan Chen, Jordan Cotler, Hsin-Yuan Huang, Jerry Li:
Exponential separations between learning with and without quantum memory. CoRR abs/2111.05881 (2021) - [i48]Jerry Li, Allen Liu:
Clustering Mixtures with Almost Optimal Separation in Polynomial Time. CoRR abs/2112.00706 (2021) - [i47]Hsin-Yuan Huang, Michael Broughton, Jordan Cotler, Sitan Chen, Jerry Li, Masoud Mohseni, Hartmut Neven, Ryan Babbush, Richard Kueng, John Preskill, Jarrod R. McClean:
Quantum advantage in learning from experiments. CoRR abs/2112.00778 (2021) - [i46]Sung Min Park, Kuo-An Wei, Kai Yuanqing Xiao, Jerry Li, Aleksander Madry:
On Distinctive Properties of Universal Perturbations. CoRR abs/2112.15329 (2021) - 2020
- [c40]Sébastien Bubeck, Sitan Chen, Jerry Li:
Entanglement is Necessary for Optimal Quantum Property Testing. FOCS 2020: 692-703 - [c39]Hannah Lawrence, Jerry Li, Cameron Musco, Christopher Musco:
Low-Rank Toeplitz Matrix Estimation Via Random Ultra-Sparse Rulers. ICASSP 2020: 4796-4800 - [c38]Greg Yang, Tony Duan, J. Edward Hu, Hadi Salman, Ilya P. Razenshteyn, Jerry Li:
Randomized Smoothing of All Shapes and Sizes. ICML 2020: 10693-10705 - [c37]Jerry Li, Guanghao Ye:
Robust Gaussian Covariance Estimation in Nearly-Matrix Multiplication Time. NeurIPS 2020 - [c36]Sitan Chen, Jerry Li, Ankur Moitra:
Learning Structured Distributions From Untrusted Batches: Faster and Simpler. NeurIPS 2020 - [c35]Samuel B. Hopkins, Jerry Li, Fred Zhang:
Robust and Heavy-Tailed Mean Estimation Made Simple, via Regret Minimization. NeurIPS 2020 - [c34]Arun Jambulapati, Jerry Li, Kevin Tian:
Robust Sub-Gaussian Principal Component Analysis and Width-Independent Schatten Packing. NeurIPS 2020 - [c33]Yonina C. Eldar, Jerry Li, Cameron Musco, Christopher Musco:
Sample Efficient Toeplitz Covariance Estimation. SODA 2020: 378-397 - [c32]Sitan Chen, Jerry Li, Zhao Song:
Learning mixtures of linear regressions in subexponential time via Fourier moments. STOC 2020: 587-600 - [c31]Arun Jambulapati, Yin Tat Lee, Jerry Li, Swati Padmanabhan, Kevin Tian:
Positive semidefinite programming: mixed, parallel, and width-independent. STOC 2020: 789-802 - [c30]Sitan Chen, Jerry Li, Ankur Moitra:
Efficiently learning structured distributions from untrusted batches. STOC 2020: 960-973 - [i45]Arun Jambulapati, Yin Tat Lee, Jerry Li, Swati Padmanabhan, Kevin Tian:
Positive Semidefinite Programming: Mixed, Parallel, and Width-Independent. CoRR abs/2002.04830 (2020) - [i44]Greg Yang, Tony Duan, J. Edward Hu, Hadi Salman, Ilya P. Razenshteyn, Jerry Li:
Randomized Smoothing of All Shapes and Sizes. CoRR abs/2002.08118 (2020) - [i43]Sitan Chen, Jerry Li, Ankur Moitra:
Learning Structured Distributions From Untrusted Batches: Faster and Simpler. CoRR abs/2002.10435 (2020) - [i42]Ilias Diakonikolas, Jerry Li, Anastasia Voloshinov:
Efficient Algorithms for Multidimensional Segmented Regression. CoRR abs/2003.11086 (2020) - [i41]Sébastien Bubeck, Sitan Chen, Jerry Li:
Entanglement is Necessary for Optimal Quantum Property Testing. CoRR abs/2004.07869 (2020) - [i40]Arun Jambulapati, Jerry Li, Kevin Tian:
Robust Sub-Gaussian Principal Component Analysis and Width-Independent Schatten Packing. CoRR abs/2006.06980 (2020) - [i39]Jerry Li, Guanghao Ye:
Robust Gaussian Covariance Estimation in Nearly-Matrix Multiplication Time. CoRR abs/2006.13312 (2020) - [i38]Ivan Evtimov, Weidong Cui, Ece Kamar, Emre Kiciman, Tadayoshi Kohno, Jerry Li:
Security and Machine Learning in the Real World. CoRR abs/2007.07205 (2020) - [i37]Samuel B. Hopkins, Jerry Li, Fred Zhang:
Robust and Heavy-Tailed Mean Estimation Made Simple, via Regret Minimization. CoRR abs/2007.15839 (2020) - [i36]Jerry Li, Aaron Sidford, Kevin Tian, Huishuai Zhang:
Well-Conditioned Methods for Ill-Conditioned Systems: Linear Regression with Semi-Random Noise. CoRR abs/2008.01722 (2020) - [i35]Dan Hendrycks, Collin Burns, Steven Basart, Andrew Critch, Jerry Li, Dawn Song, Jacob Steinhardt:
Aligning AI With Shared Human Values. CoRR abs/2008.02275 (2020) - [i34]Matthew S. Brennan, Guy Bresler, Samuel B. Hopkins, Jerry Li, Tselil Schramm:
Statistical Query Algorithms and Low-Degree Tests Are Almost Equivalent. CoRR abs/2009.06107 (2020) - [i33]Ilias Diakonikolas, Daniel M. Kane, Daniel Kongsgaard, Jerry Li, Kevin Tian:
List-Decodable Mean Estimation in Nearly-PCA Time. CoRR abs/2011.09973 (2020) - [i32]Zeyuan Allen-Zhu, Faeze Ebrahimian, Jerry Li, Dan Alistarh:
Byzantine-Resilient Non-Convex Stochastic Gradient Descent. CoRR abs/2012.14368 (2020)
2010 – 2019
- 2019
- [j2]Ilias Diakonikolas, Gautam Kamath, Daniel Kane, Jerry Li, Ankur Moitra, Alistair Stewart:
Robust Estimators in High-Dimensions Without the Computational Intractability. SIAM J. Comput. 48(2): 742-864 (2019) - [c29]Samuel B. Hopkins, Jerry Li:
How Hard is Robust Mean Estimation? COLT 2019: 1649-1682 - [c28]Gautam Kamath, Jerry Li, Vikrant Singhal, Jonathan R. Ullman:
Privately Learning High-Dimensional Distributions. COLT 2019: 1853-1902 - [c27]Jerry Li, Aleksandar Nikolov, Ilya P. Razenshteyn, Erik Waingarten:
On Mean Estimation for General Norms with Statistical Queries. COLT 2019: 2158-2172 - [c26]Ilias Diakonikolas, Gautam Kamath, Daniel Kane, Jerry Li, Jacob Steinhardt, Alistair Stewart:
Sever: A Robust Meta-Algorithm for Stochastic Optimization. ICML 2019: 1596-1606 - [c25]Yihe Dong, Samuel B. Hopkins, Jerry Li:
Quantum Entropy Scoring for Fast Robust Mean Estimation and Improved Outlier Detection. NeurIPS 2019: 6065-6075 - [c24]Hadi Salman, Jerry Li, Ilya P. Razenshteyn, Pengchuan Zhang, Huan Zhang, Sébastien Bubeck, Greg Yang:
Provably Robust Deep Learning via Adversarially Trained Smoothed Classifiers. NeurIPS 2019: 11289-11300 - [i31]Jerry Li, Aleksandar Nikolov, Ilya P. Razenshteyn, Erik Waingarten:
On Mean Estimation for General Norms with Statistical Queries. CoRR abs/1902.02459 (2019) - [i30]Samuel B. Hopkins, Jerry Li:
How Hard Is Robust Mean Estimation? CoRR abs/1903.07870 (2019) - [i29]Yonina C. Eldar, Jerry Li, Cameron Musco, Christopher Musco:
Sample Efficient Toeplitz Covariance Estimation. CoRR abs/1905.05643 (2019) - [i28]Hadi Salman, Greg Yang, Jerry Li, Pengchuan Zhang, Huan Zhang, Ilya P. Razenshteyn, Sébastien Bubeck:
Provably Robust Deep Learning via Adversarially Trained Smoothed Classifiers. CoRR abs/1906.04584 (2019) - [i27]Yihe Dong, Samuel B. Hopkins, Jerry Li:
Quantum Entropy Scoring for Fast Robust Mean Estimation and Improved Outlier Detection. CoRR abs/1906.11366 (2019) - [i26]Sitan Chen, Jerry Li, Ankur Moitra:
Efficiently Learning Structured Distributions from Untrusted Batches. CoRR abs/1911.02035 (2019) - [i25]Hannah Lawrence, Jerry Li, Cameron Musco, Christopher Musco:
Low-Rank Toeplitz Matrix Estimation via Random Ultra-Sparse Rulers. CoRR abs/1911.08015 (2019) - [i24]Sitan Chen, Jerry Li, Zhao Song:
Learning Mixtures of Linear Regressions in Subexponential Time via Fourier Moments. CoRR abs/1912.07629 (2019) - [i23]Jasper C. H. Lee, Jerry Li, Christopher Musco, Jeff M. Phillips, Wai Ming Tai:
Finding the Mode of a Kernel Density Estimate. CoRR abs/1912.07673 (2019) - 2018
- [b1]Jerry Zheng Li:
Principled approaches to robust machine learning and beyond. Massachusetts Institute of Technology, Cambridge, USA, 2018 - [c23]Ilias Diakonikolas, Jerry Li, Ludwig Schmidt:
Fast and Sample Near-Optimal Algorithms for Learning Multidimensional Histograms. COLT 2018: 819-842 - [c22]Jerry Li, Aleksander Madry, John Peebles, Ludwig Schmidt:
On the Limitations of First-Order Approximation in GAN Dynamics. ICML 2018: 3011-3019 - [c21]Dan Alistarh, Zeyuan Allen-Zhu, Jerry Li:
Byzantine Stochastic Gradient Descent. NeurIPS 2018: 4618-4628 - [c20]Brandon Tran, Jerry Li, Aleksander Madry:
Spectral Signatures in Backdoor Attacks. NeurIPS 2018: 8011-8021 - [c19]Ilias Diakonikolas, Gautam Kamath, Daniel M. Kane, Jerry Li, Ankur Moitra, Alistair Stewart:
Robustly Learning a Gaussian: Getting Optimal Error, Efficiently. SODA 2018: 2683-2702 - [c18]Dan Alistarh, Trevor Brown, Justin Kopinsky, Jerry Zheng Li, Giorgi Nadiradze:
Distributionally Linearizable Data Structures. SPAA 2018: 133-142 - [c17]Samuel B. Hopkins, Jerry Li:
Mixture models, robustness, and sum of squares proofs. STOC 2018: 1021-1034 - [i22]Ilias Diakonikolas, Jerry Li, Ludwig Schmidt:
Fast and Sample Near-Optimal Algorithms for Learning Multidimensional Histograms. CoRR abs/1802.08513 (2018) - [i21]Ilias Diakonikolas, Gautam Kamath, Daniel M. Kane, Jerry Li, Jacob Steinhardt, Alistair Stewart:
Sever: A Robust Meta-Algorithm for Stochastic Optimization. CoRR abs/1803.02815 (2018) - [i20]Dan Alistarh, Zeyuan Allen-Zhu, Jerry Li:
Byzantine Stochastic Gradient Descent. CoRR abs/1803.08917 (2018) - [i19]Dan Alistarh, Trevor Brown, Justin Kopinsky, Jerry Zheng Li, Giorgi Nadiradze:
Distributionally Linearizable Data Structures. CoRR abs/1804.01018 (2018) - [i18]Gautam Kamath, Jerry Li, Vikrant Singhal, Jonathan R. Ullman:
Privately Learning High-Dimensional Distributions. CoRR abs/1805.00216 (2018) - [i17]Brandon Tran, Jerry Li, Aleksander Madry:
Spectral Signatures in Backdoor Attacks. CoRR abs/1811.00636 (2018) - 2017
- [j1]Paul Beame, Jerry Li, Sudeepa Roy, Dan Suciu:
Exact Model Counting of Query Expressions: Limitations of Propositional Methods. ACM Trans. Database Syst. 42(1): 1:1-1:46 (2017) - [c16]Sivaraman Balakrishnan, Simon S. Du, Jerry Li, Aarti Singh:
Computationally Efficient Robust Sparse Estimation in High Dimensions. COLT 2017: 169-212 - [c15]Jerry Li, Ludwig Schmidt:
Robust and Proper Learning for Mixtures of Gaussians via Systems of Polynomial Inequalities. COLT 2017: 1302-1382 - [c14]Ilias Diakonikolas, Gautam Kamath, Daniel M. Kane, Jerry Li, Ankur Moitra, Alistair Stewart:
Being Robust (in High Dimensions) Can Be Practical. ICML 2017: 999-1008 - [c13]Hantian Zhang, Jerry Li, Kaan Kara, Dan Alistarh, Ji Liu, Ce Zhang:
ZipML: Training Linear Models with End-to-End Low Precision, and a Little Bit of Deep Learning. ICML 2017: 4035-4043 - [c12]Dan Alistarh, Demjan Grubic, Jerry Li, Ryota Tomioka, Milan Vojnovic:
QSGD: Communication-Efficient SGD via Gradient Quantization and Encoding. NIPS 2017: 1709-1720 - [c11]Ilias Diakonikolas, Elena Grigorescu, Jerry Li, Abhiram Natarajan, Krzysztof Onak, Ludwig Schmidt:
Communication-Efficient Distributed Learning of Discrete Distributions. NIPS 2017: 6391-6401 - [c10]Dan Alistarh, Justin Kopinsky, Jerry Li, Giorgi Nadiradze:
The Power of Choice in Priority Scheduling. PODC 2017: 283-292 - [c9]Jayadev Acharya, Ilias Diakonikolas, Jerry Li, Ludwig Schmidt:
Sample-Optimal Density Estimation in Nearly-Linear Time. SODA 2017: 1278-1289 - [i16]Jerry Li:
Robust Sparse Estimation Tasks in High Dimensions. CoRR abs/1702.05860 (2017) - [i15]Ilias Diakonikolas, Gautam Kamath, Daniel M. Kane, Jerry Li, Ankur Moitra, Alistair Stewart:
Being Robust (in High Dimensions) Can Be Practical. CoRR abs/1703.00893 (2017) - [i14]Ilias Diakonikolas, Gautam Kamath, Daniel M. Kane, Jerry Li, Ankur Moitra, Alistair Stewart:
Robustly Learning a Gaussian: Getting Optimal Error, Efficiently. CoRR abs/1704.03866 (2017) - [i13]Dan Alistarh, Justin Kopinsky, Jerry Li, Giorgi Nadiradze:
The Power of Choice in Priority Scheduling. CoRR abs/1706.04178 (2017) - [i12]Jerry Li, Aleksander Madry, John Peebles, Ludwig Schmidt:
Towards Understanding the Dynamics of Generative Adversarial Networks. CoRR abs/1706.09884 (2017) - [i11]Samuel B. Hopkins, Jerry Li:
Mixture Models, Robustness, and Sum of Squares Proofs. CoRR abs/1711.07454 (2017) - 2016
- [c8]Ilias Diakonikolas, Gautam Kamath, Daniel M. Kane, Jerry Li, Ankur Moitra, Alistair Stewart:
Robust Estimators in High Dimensions without the Computational Intractability. FOCS 2016: 655-664 - [c7]Jayadev Acharya, Ilias Diakonikolas, Jerry Li, Ludwig Schmidt:
Fast Algorithms for Segmented Regression. ICML 2016: 2878-2886 - [i10]Ilias Diakonikolas, Gautam Kamath, Daniel M. Kane, Jerry Zheng Li, Ankur Moitra, Alistair Stewart:
Robust Estimators in High Dimensions without the Computational Intractability. CoRR abs/1604.06443 (2016) - [i9]Jayadev Acharya, Ilias Diakonikolas, Jerry Li, Ludwig Schmidt:
Fast Algorithms for Segmented Regression. CoRR abs/1607.03990 (2016) - [i8]Dan Alistarh, Jerry Li, Ryota Tomioka, Milan Vojnovic:
QSGD: Randomized Quantization for Communication-Optimal Stochastic Gradient Descent. CoRR abs/1610.02132 (2016) - [i7]Hantian Zhang, Kaan Kara, Jerry Li, Dan Alistarh, Ji Liu, Ce Zhang:
ZipML: An End-to-end Bitwise Framework for Dense Generalized Linear Models. CoRR abs/1611.05402 (2016) - 2015
- [c6]Jerry Li, John Peebles:
Replacing Mark Bits with Randomness in Fibonacci Heaps. ICALP (1) 2015: 886-897 - [c5]Jayadev Acharya, Ilias Diakonikolas, Chinmay Hegde, Jerry Zheng Li, Ludwig Schmidt:
Fast and Near-Optimal Algorithms for Approximating Distributions by Histograms. PODS 2015: 249-263 - [c4]Dan Alistarh, Justin Kopinsky, Jerry Li, Nir Shavit:
The SprayList: a scalable relaxed priority queue. PPoPP 2015: 11-20 - [i6]Jayadev Acharya, Ilias Diakonikolas, Jerry Zheng Li, Ludwig Schmidt:
Sample-Optimal Density Estimation in Nearly-Linear Time. CoRR abs/1506.00671 (2015) - [i5]Jerry Zheng Li, Ludwig Schmidt:
A Nearly Optimal and Agnostic Algorithm for Properly Learning a Mixture of k Gaussians, for any Constant k. CoRR abs/1506.01367 (2015) - 2014
- [c3]Paul Beame, Jerry Li, Sudeepa Roy, Dan Suciu:
Counting of Query Expressions: Limitations of Propositional Methods. ICDT 2014: 177-188 - [c2]Rati Gelashvili, Mohsen Ghaffari, Jerry Li, Nir Shavit:
On the Importance of Registers for Computability. OPODIS 2014: 171-185 - [i4]Jerry Li, John Peebles:
Replacing Mark Bits with Randomness in Fibonacci Heaps. CoRR abs/1407.2569 (2014) - [i3]Rati Gelashvili, Mohsen Ghaffari, Jerry Li, Nir Shavit:
On the Importance of Registers for Computability. CoRR abs/1411.0168 (2014) - 2013
- [c1]Paul Beame, Jerry Li, Sudeepa Roy, Dan Suciu:
Lower Bounds for Exact Model Counting and Applications in Probabilistic Databases. UAI 2013 - [i2]Paul Beame, Jerry Li, Sudeepa Roy, Dan Suciu:
Lower Bounds for Exact Model Counting and Applications in Probabilistic Databases. CoRR abs/1309.6815 (2013) - [i1]Paul Beame, Jerry Li, Sudeepa Roy, Dan Suciu:
Model Counting of Query Expressions: Limitations of Propositional Methods. CoRR abs/1312.4125 (2013)
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2026-07-31 23:51 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated, funded, and maintained by:
Schloss Dagstuhl - Leibniz Center for Informatics is a member of the Leibniz Association and is funded by the federal government of Germany and the states of Germany, especially Saarland and Rhineland‑Palatinate.
