Jerry Li

ORCID

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 126

Top Venues

Publications

Arun Jambulapati, Syamantak Kumar, Jerry Li, Shourya Pandey, Ankit Pensia, Kevin Tian
Black-Box k-to-1-PCA Reductions: Theory and Applications. COLT (2024)
Sitan Chen, Jerry Li, Allen Liu
An Optimal Tradeoff between Entanglement and Copy Complexity for State Tomography. STOC (2024)
Arun Jambulapati, Syamantak Kumar, Jerry Li, Shourya Pandey, Ankit Pensia, Kevin Tian
Black-Box k-to-1-PCA Reductions: Theory and Applications. CoRR (2024)
Sinho Chewi, Jaume de Dios Pont, Jerry Li, Chen Lu, Shyam Narayanan
Query Lower Bounds for Log-concave Sampling. J. ACM 71 (4) (2024)
Sitan Chen, Jerry Li, Allen Liu
An optimal tradeoff between entanglement and copy complexity for state tomography. CoRR (2024)
Jonathan A. Kelner, Jerry Li, Allen X. Liu, Aaron Sidford, Kevin Tian
Semi-Random Sparse Recovery in Nearly-Linear Time. COLT (2023)
Jonathan A. Kelner, Jerry Li, Allen Liu, Aaron Sidford, Kevin Tian
Matrix Completion in Almost-Verification Time. CoRR (2023)
Reid Pryzant, Dan Iter, Jerry Li, Yin Tat Lee, Chenguang Zhu, Michael Zeng
Automatic Prompt Optimization with "Gradient Descent" and Beam Search. CoRR (2023)
Arun Jambulapati, Jerry Li, Christopher Musco, Kirankumar Shiragur, Aaron Sidford, Kevin Tian
Structured Semidefinite Programming for Recovering Structured Preconditioners. CoRR (2023)
Arun Jambulapati, Jerry Li, Christopher Musco, Kirankumar Shiragur, Aaron Sidford, Kevin Tian
Structured Semidefinite Programming for Recovering Structured Preconditioners. NeurIPS (2023)
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)
Sinho Chewi, Jaume de Dios Pont, Jerry Li, Chen Lu, Shyam Narayanan
Query lower bounds for log-concave sampling. CoRR (2023)
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 (2023)
Sinho Chewi, Jaume de Dios Pont, Jerry Li, Chen Lu, Shyam Narayanan
Query lower bounds for log-concave sampling. FOCS (2023)
Jonathan A. Kelner, Jerry Li, Allen Liu, Aaron Sidford, Kevin Tian
Matrix Completion in Almost-Verification Time. FOCS (2023)
Sitan Chen, Brice Huang, Jerry Li, Allen Liu, Mark Sellke
When Does Adaptivity Help for Quantum State Learning? FOCS (2023)
Reid Pryzant, Dan Iter, Jerry Li, Yin Tat Lee, Chenguang Zhu, Michael Zeng
Automatic Prompt Optimization with "Gradient Descent" and Beam Search. EMNLP (2023)
Sitan Chen, Jerry Li, Yuanzhi Li, Anru R. Zhang
Learning Polynomial Transformations via Generalized Tensor Decompositions. STOC (2023)
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)
Sitan Chen, Jerry Li, Yuanzhi Li, Raghu Meka
Minimax Optimality (Probably) Doesn't Imply Distribution Learning for GANs. CoRR (2022)
Sitan Chen, Brice Huang, Jerry Li, Allen Liu
Tight Bounds for Quantum State Certification with Incoherent Measurements. CoRR (2022)
Sitan Chen, Jerry Li, Yuanzhi Li, Raghu Meka
Minimax Optimality (Probably) Doesn't Imply Distribution Learning for GANs. ICLR (2022)
Sitan Chen, Brice Huang, Jerry Li, Allen Liu, Mark Sellke
Tight Bounds for State Tomography with Incoherent Measurements. CoRR (2022)
Sitan Chen, Jordan Cotler, Hsin-Yuan Huang, Jerry Li
The Complexity of NISQ. CoRR (2022)
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 (2022)
Sitan Chen, Jerry Li, Ryan O'Donnell
Toward Instance-Optimal State Certification With Incoherent Measurements. COLT (2022)
Sitan Chen, Jordan Cotler, Hsin-Yuan Huang, Jerry Li
Exponential Separations Between Learning With and Without Quantum Memory. FOCS (2022)
Sitan Chen, Jerry Li, Yuanzhi Li, Anru R. Zhang
Learning Polynomial Transformations. CoRR (2022)
Allen Liu, Jerry Li, Ankur Moitra
Robust Model Selection and Nearly-Proper Learning for GMMs. NeurIPS (2022)
Sitan Chen, Jerry Li, Yuanzhi Li
Learning (Very) Simple Generative Models Is Hard. CoRR (2022)
Clément L. Canonne, Ayush Jain, Gautam Kamath, Jerry Li
The Price of Tolerance in Distribution Testing. COLT (2022)
Sitan Chen, Jerry Li, Brice Huang, Allen Liu
Tight Bounds for Quantum State Certification with Incoherent Measurements. FOCS (2022)
Jonathan A. Kelner, Jerry Li, Allen Liu, Aaron Sidford, Kevin Tian
Semi-Random Sparse Recovery in Nearly-Linear Time. CoRR (2022)
Sitan Chen, Jerry Li, Yuanzhi Li
Learning (Very) Simple Generative Models Is Hard. NeurIPS (2022)
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)
Allen Liu, Jerry Li
Clustering mixtures with almost optimal separation in polynomial time. STOC (2022)
Dan Hendrycks, Collin Burns, Steven Basart, Andrew Critch, Jerry Li, Dawn Song, Jacob Steinhardt
Aligning AI With Shared Human Values. ICLR (2021)
Sitan Chen, Jordan Cotler, Hsin-Yuan Huang, Jerry Li
Exponential separations between learning with and without quantum memory. CoRR (2021)
Sung Min Park, Kuo-An Wei, Kai Yuanqing Xiao, Jerry Li, Aleksander Madry
On Distinctive Properties of Universal Perturbations. CoRR (2021)
Arun Jambulapati, Jerry Li, Tselil Schramm, Kevin Tian
Robust Regression Revisited: Acceleration and Improved Estimation Rates. CoRR (2021)
Arun Jambulapati, Jerry Li, Tselil Schramm, Kevin Tian
Robust Regression Revisited: Acceleration and Improved Estimation Rates. NeurIPS (2021)
Ilias Diakonikolas, Daniel M. Kane, Daniel Kongsgaard, Jerry Li, Kevin Tian
Clustering Mixture Models in Almost-Linear Time via List-Decodable Mean Estimation. CoRR (2021)
Clément L. Canonne, Ayush Jain, Gautam Kamath, Jerry Li
The Price of Tolerance in Distribution Testing. CoRR (2021)
Sitan Chen, Jordan Cotler, Hsin-Yuan Huang, Jerry Li
Exponential Separations Between Learning With and Without Quantum Memory. FOCS (2021)
Matthew S. Brennan, Guy Bresler, Samuel B. Hopkins, Jerry Li, Tselil Schramm
Statistical Query Algorithms and Low Degree Tests Are Almost Equivalent. COLT (2021)
Jerry Li, Allen Liu, Ankur Moitra
Sparsification for Sums of Exponentials and its Algorithmic Applications. CoRR (2021)
Ilias Diakonikolas, Gautam Kamath, Daniel M. Kane, Jerry Li, Ankur Moitra, Alistair Stewart
Robustness meets algorithms. Commun. ACM 64 (5) (2021)
Zeyuan Allen-Zhu, Faeze Ebrahimianghazani, Jerry Li, Dan Alistarh
Byzantine-Resilient Non-Convex Stochastic Gradient Descent. ICLR (2021)
Ilias Diakonikolas, Daniel Kane, Daniel Kongsgaard, Jerry Li, Kevin Tian
List-Decodable Mean Estimation in Nearly-PCA Time. NeurIPS (2021)
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 (2021)
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)
Sitan Chen, Jerry Li, Ryan O'Donnell
Toward Instance-Optimal State Certification With Incoherent Measurements. CoRR (2021)
Sitan Chen, Jordan Cotler, Hsin-Yuan Huang, Jerry Li
A Hierarchy for Replica Quantum Advantage. CoRR (2021)
Jerry Li, Allen Liu
Clustering Mixtures with Almost Optimal Separation in Polynomial Time. CoRR (2021)
Samuel B. Hopkins, Jerry Li, Fred Zhang
Robust and Heavy-Tailed Mean Estimation Made Simple, via Regret Minimization. CoRR (2020)
Ilias Diakonikolas, Jerry Li, Anastasia Voloshinov
Efficient Algorithms for Multidimensional Segmented Regression. CoRR (2020)
Sitan Chen, Jerry Li, Ankur Moitra
Learning Structured Distributions From Untrusted Batches: Faster and Simpler. NeurIPS (2020)
Zeyuan Allen-Zhu, Faeze Ebrahimian, Jerry Li, Dan Alistarh
Byzantine-Resilient Non-Convex Stochastic Gradient Descent. CoRR (2020)
Samuel B. Hopkins, Jerry Li, Fred Zhang
Robust and Heavy-Tailed Mean Estimation Made Simple, via Regret Minimization. NeurIPS (2020)
Ilias Diakonikolas, Daniel M. Kane, Daniel Kongsgaard, Jerry Li, Kevin Tian
List-Decodable Mean Estimation in Nearly-PCA Time. CoRR (2020)
Yonina C. Eldar, Jerry Li, Cameron Musco, Christopher Musco
Sample Efficient Toeplitz Covariance Estimation. SODA (2020)
Jerry Li, Guanghao Ye
Robust Gaussian Covariance Estimation in Nearly-Matrix Multiplication Time. NeurIPS (2020)
Sébastien Bubeck, Sitan Chen, Jerry Li
Entanglement is Necessary for Optimal Quantum Property Testing. FOCS (2020)
Arun Jambulapati, Jerry Li, Kevin Tian
Robust Sub-Gaussian Principal Component Analysis and Width-Independent Schatten Packing. CoRR (2020)
Jerry Li, Guanghao Ye
Robust Gaussian Covariance Estimation in Nearly-Matrix Multiplication Time. CoRR (2020)
Sitan Chen, Jerry Li, Ankur Moitra
Learning Structured Distributions From Untrusted Batches: Faster and Simpler. CoRR (2020)
Arun Jambulapati, Jerry Li, Kevin Tian
Robust Sub-Gaussian Principal Component Analysis and Width-Independent Schatten Packing. NeurIPS (2020)
Hannah Lawrence, Jerry Li, Cameron Musco, Christopher Musco
Low-Rank Toeplitz Matrix Estimation Via Random Ultra-Sparse Rulers. ICASSP (2020)
Dan Hendrycks, Collin Burns, Steven Basart, Andrew Critch, Jerry Li, Dawn Song, Jacob Steinhardt
Aligning AI With Shared Human Values. CoRR (2020)
Sitan Chen, Jerry Li, Ankur Moitra
Efficiently learning structured distributions from untrusted batches. STOC (2020)
Arun Jambulapati, Yin Tat Lee, Jerry Li, Swati Padmanabhan, Kevin Tian
Positive Semidefinite Programming: Mixed, Parallel, and Width-Independent. CoRR (2020)
Sitan Chen, Jerry Li, Zhao Song
Learning mixtures of linear regressions in subexponential time via Fourier moments. STOC (2020)
Matthew S. Brennan, Guy Bresler, Samuel B. Hopkins, Jerry Li, Tselil Schramm
Statistical Query Algorithms and Low-Degree Tests Are Almost Equivalent. CoRR (2020)
Greg Yang, Tony Duan, J. Edward Hu, Hadi Salman, Ilya P. Razenshteyn, Jerry Li
Randomized Smoothing of All Shapes and Sizes. CoRR (2020)
Greg Yang, Tony Duan, J. Edward Hu, Hadi Salman, Ilya P. Razenshteyn, Jerry Li
Randomized Smoothing of All Shapes and Sizes. ICML (2020)
Sébastien Bubeck, Sitan Chen, Jerry Li
Entanglement is Necessary for Optimal Quantum Property Testing. CoRR (2020)
Ivan Evtimov, Weidong Cui, Ece Kamar, Emre Kiciman, Tadayoshi Kohno, Jerry Li
Security and Machine Learning in the Real World. CoRR (2020)
Jerry Li, Aaron Sidford, Kevin Tian, Huishuai Zhang
Well-Conditioned Methods for Ill-Conditioned Systems: Linear Regression with Semi-Random Noise. CoRR (2020)
Arun Jambulapati, Yin Tat Lee, Jerry Li, Swati Padmanabhan, Kevin Tian
Positive semidefinite programming: mixed, parallel, and width-independent. STOC (2020)
Ilias Diakonikolas, Gautam Kamath, Daniel Kane, Jerry Li, Jacob Steinhardt, Alistair Stewart
Sever: A Robust Meta-Algorithm for Stochastic Optimization. ICML (2019)
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) (2019)
Hannah Lawrence, Jerry Li, Cameron Musco, Christopher Musco
Low-Rank Toeplitz Matrix Estimation via Random Ultra-Sparse Rulers. CoRR (2019)
Yonina C. Eldar, Jerry Li, Cameron Musco, Christopher Musco
Sample Efficient Toeplitz Covariance Estimation. CoRR (2019)
Sitan Chen, Jerry Li, Zhao Song
Learning Mixtures of Linear Regressions in Subexponential Time via Fourier Moments. CoRR (2019)
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)
Jasper C. H. Lee, Jerry Li, Christopher Musco, Jeff M. Phillips, Wai Ming Tai
Finding the Mode of a Kernel Density Estimate. CoRR (2019)
Yihe Dong, Samuel B. Hopkins, Jerry Li
Quantum Entropy Scoring for Fast Robust Mean Estimation and Improved Outlier Detection. NeurIPS (2019)
Sitan Chen, Jerry Li, Ankur Moitra
Efficiently Learning Structured Distributions from Untrusted Batches. CoRR (2019)
Samuel B. Hopkins, Jerry Li
How Hard is Robust Mean Estimation? COLT (2019)
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 (2019)
Jerry Li, Aleksandar Nikolov, Ilya P. Razenshteyn, Erik Waingarten
On Mean Estimation for General Norms with Statistical Queries. COLT (2019)
Samuel B. Hopkins, Jerry Li
How Hard Is Robust Mean Estimation? CoRR (2019)
Jerry Li, Aleksandar Nikolov, Ilya P. Razenshteyn, Erik Waingarten
On Mean Estimation for General Norms with Statistical Queries. CoRR (2019)
Yihe Dong, Samuel B. Hopkins, Jerry Li
Quantum Entropy Scoring for Fast Robust Mean Estimation and Improved Outlier Detection. CoRR (2019)
Gautam Kamath, Jerry Li, Vikrant Singhal, Jonathan R. Ullman
Privately Learning High-Dimensional Distributions. COLT (2019)
Ilias Diakonikolas, Jerry Li, Ludwig Schmidt
Fast and Sample Near-Optimal Algorithms for Learning Multidimensional Histograms. CoRR (2018)
Ilias Diakonikolas, Gautam Kamath, Daniel M. Kane, Jerry Li, Ankur Moitra, Alistair Stewart
Robustly Learning a Gaussian: Getting Optimal Error, Efficiently. SODA (2018)
Ilias Diakonikolas, Jerry Li, Ludwig Schmidt
Fast and Sample Near-Optimal Algorithms for Learning Multidimensional Histograms. COLT (2018)
Dan Alistarh, Zeyuan Allen-Zhu, Jerry Li
Byzantine Stochastic Gradient Descent. CoRR (2018)
Jerry Li, Aleksander Madry, John Peebles, Ludwig Schmidt
On the Limitations of First-Order Approximation in GAN Dynamics. ICML (2018)

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Publication Activity (10 Years)

Top Topics

Top Venues

Jerry Li