Li, Jerry

51 publications

CoRL 2025 BEVCalib: LiDAR-Camera Calibration via Geometry-Guided Bird’s-Eye View Representation Weiduo Yuan, Jerry Li, Justin Yue, Divyank Shah, Konstantinos Karydis, Hang Qiu

COLT 2025 Predicting Quantum Channels over General Product Distributions Sitan Chen, Jaume de Dios Pont, Jun-Ting Hsieh, Hsin-Yuan Huang, Jane Lange, Jerry Li

NeurIPS 2025 Robust Estimation Under Heterogeneous Corruption Rates Syomantak Chaudhuri, Jerry Li, Thomas Courtade

ICML 2025 S4S: Solving for a Fast Diffusion Model Solver Eric Frankel, Sitan Chen, Jerry Li, Pang Wei Koh, Lillian J. Ratliff, Sewoong Oh

ICLRW 2025 The Delta Learning Hypothesis: Preference Tuning on Weak Data Can Yield Strong Gains Scott Geng, Hamish Ivison, Chun-Liang Li, Maarten Sap, Jerry Li, Ranjay Krishna, Pang Wei Koh

COLT 2024 Black-Box K-to-1-PCA Reductions: Theory and Applications Arun Jambulapati, Syamantak Kumar, Jerry Li, Shourya Pandey, Ankit Pensia, Kevin Tian

ICLR 2024 KITAB: Evaluating LLMs on Constraint Satisfaction for Information Retrieval Marah I Abdin, Suriya Gunasekar, Varun Chandrasekaran, Jerry Li, Mert Yuksekgonul, Rahee Ghosh Peshawaria, Ranjita Naik, Besmira Nushi

ICMLW 2024 Long Context Understanding Using Self-Generated Synthetic Data Jerry Li, Subhro Das, Aude Oliva, Dmitry Krotov, Leonid Karlinsky, Rogerio Feris

NeurIPS 2024 Semi-Random Matrix Completion via Flow-Based Adaptive Reweighting Jonathan A. Kelner, Jerry Li, Allen Liu, Aaron Sidford, Kevin Tian

ICCV 2023 REAP: A Large-Scale Realistic Adversarial Patch Benchmark Nabeel Hingun, Chawin Sitawarin, Jerry Li, David Wagner

ICLR 2023 Sampling Is as Easy as Learning the Score: Theory for Diffusion Models with Minimal Data Assumptions Sitan Chen, Sinho Chewi, Jerry Li, Yuanzhi Li, Adil Salim, Anru Zhang

COLT 2023 Semi-Random Sparse Recovery in Nearly-Linear Time Jonathan Kelner, Jerry Li, Allen X. Liu, Aaron Sidford, Kevin Tian

NeurIPS 2023 Structured Semidefinite Programming for Recovering Structured Preconditioners Arun Jambulapati, Jerry Li, Christopher Musco, Kirankumar Shiragur, Aaron Sidford, Kevin Tian

NeurIPS 2022 Learning (Very) Simple Generative Models Is Hard Sitan Chen, Jerry Li, Yuanzhi Li

ICLR 2022 Minimax Optimality (Probably) Doesn't Imply Distribution Learning for GANs Sitan Chen, Jerry Li, Yuanzhi Li, Raghu Meka

NeurIPSW 2022 REAP: A Large-Scale Realistic Adversarial Patch Benchmark Nabeel Hingun, Chawin Sitawarin, Jerry Li, David Wagner

NeurIPS 2022 Robust Model Selection and Nearly-Proper Learning for GMMs Allen Liu, Jerry Li, Ankur Moitra

NeurIPSW 2022 Sampling Is as Easy as Learning the Score: Theory for Diffusion Models with Minimal Data Assumptions Sitan Chen, Sinho Chewi, Jerry Li, Yuanzhi Li, Adil Salim, Anru Zhang

NeurIPSW 2022 Semi-Random Sparse Recovery in Nearly-Linear Time Jonathan Kelner, Jerry Li, Allen Liu, Aaron Sidford, Kevin Tian

COLT 2022 The Price of Tolerance in Distribution Testing Clement L Canonne, Ayush Jain, Gautam Kamath, Jerry Li

COLT 2022 Toward Instance-Optimal State Certification with Incoherent Measurements Sitan Chen, Jerry Li, Ryan O’Donnell

ICLR 2021 Aligning AI with Shared Human Values Dan Hendrycks, Collin Burns, Steven Basart, Andrew Critch, Jerry Li, Dawn Song, Jacob Steinhardt

ICLR 2021 Byzantine-Resilient Non-Convex Stochastic Gradient Descent Zeyuan Allen-Zhu, Faeze Ebrahimianghazani, Jerry Li, Dan Alistarh

MLJ 2021 Challenges of Real-World Reinforcement Learning: Definitions, Benchmarks and Analysis Gabriel Dulac-Arnold, Nir Levine, Daniel J. Mankowitz, Jerry Li, Cosmin Paduraru, Sven Gowal, Todd Hester

NeurIPS 2021 List-Decodable Mean Estimation in Nearly-PCA Time Ilias Diakonikolas, Daniel Kane, Daniel Kongsgaard, Jerry Li, Kevin Tian

NeurIPS 2021 Robust Regression Revisited: Acceleration and Improved Estimation Rates Arun Jambulapati, Jerry Li, Tselil Schramm, Kevin Tian

COLT 2021 Statistical Query Algorithms and Low Degree Tests Are Almost Equivalent Matthew S Brennan, Guy Bresler, Sam Hopkins, Jerry Li, Tselil Schramm

NeurIPS 2020 Learning Structured Distributions from Untrusted Batches: Faster and Simpler Sitan Chen, Jerry Li, Ankur Moitra

NeurIPS 2020 RL Unplugged: A Suite of Benchmarks for Offline Reinforcement Learning Caglar Gulcehre, Ziyu Wang, Alexander Novikov, Thomas Paine, Sergio Gómez, Konrad Zolna, Rishabh Agarwal, Josh S Merel, Daniel J Mankowitz, Cosmin Paduraru, Gabriel Dulac-Arnold, Jerry Li, Mohammad Norouzi, Matthew Hoffman, Nicolas Heess, Nando de Freitas

ICML 2020 Randomized Smoothing of All Shapes and Sizes Greg Yang, Tony Duan, J. Edward Hu, Hadi Salman, Ilya Razenshteyn, Jerry Li

NeurIPS 2020 Robust Gaussian Covariance Estimation in Nearly-Matrix Multiplication Time Jerry Li, Guanghao Ye

NeurIPS 2020 Robust Sub-Gaussian Principal Component Analysis and Width-Independent Schatten Packing Arun Jambulapati, Jerry Li, Kevin Tian

NeurIPS 2020 Robust and Heavy-Tailed Mean Estimation Made Simple, via Regret Minimization Sam Hopkins, Jerry Li, Fred Zhang

COLT 2019 How Hard Is Robust Mean Estimation? Samuel B. Hopkins, Jerry Li

COLT 2019 On Mean Estimation for General Norms with Statistical Queries Jerry Li, Aleksandar Nikolov, Ilya Razenshteyn, Erik Waingarten

COLT 2019 Privately Learning High-Dimensional Distributions Gautam Kamath, Jerry Li, Vikrant Singhal, Jonathan Ullman

NeurIPS 2019 Provably Robust Deep Learning via Adversarially Trained Smoothed Classifiers Hadi Salman, Jerry Li, Ilya Razenshteyn, Pengchuan Zhang, Huan Zhang, Sebastien Bubeck, Greg Yang

NeurIPS 2019 Quantum Entropy Scoring for Fast Robust Mean Estimation and Improved Outlier Detection Yihe Dong, Samuel Hopkins, Jerry Li

ICML 2019 Sever: A Robust Meta-Algorithm for Stochastic Optimization Ilias Diakonikolas, Gautam Kamath, Daniel Kane, Jerry Li, Jacob Steinhardt, Alistair Stewart

NeurIPS 2018 Byzantine Stochastic Gradient Descent Dan Alistarh, Zeyuan Allen-Zhu, Jerry Li

COLT 2018 Fast and Sample Near-Optimal Algorithms for Learning Multidimensional Histograms Ilias Diakonikolas, Jerry Li, Ludwig Schmidt

ICML 2018 On the Limitations of First-Order Approximation in GAN Dynamics Jerry Li, Aleksander Madry, John Peebles, Ludwig Schmidt

NeurIPS 2018 Spectral Signatures in Backdoor Attacks Brandon Tran, Jerry Li, Aleksander Madry

ICML 2017 Being Robust (in High Dimensions) Can Be Practical Ilias Diakonikolas, Gautam Kamath, Daniel M. Kane, Jerry Li, Ankur Moitra, Alistair Stewart

NeurIPS 2017 Communication-Efficient Distributed Learning of Discrete Distributions Ilias Diakonikolas, Elena Grigorescu, Jerry Li, Abhiram Natarajan, Krzysztof Onak, Ludwig Schmidt

COLT 2017 Computationally Efficient Robust Sparse Estimation in High Dimensions Sivaraman Balakrishnan, Simon S. Du, Jerry Li, Aarti Singh

NeurIPS 2017 QSGD: Communication-Efficient SGD via Gradient Quantization and Encoding Dan Alistarh, Demjan Grubic, Jerry Li, Ryota Tomioka, Milan Vojnovic

COLT 2017 Robust and Proper Learning for Mixtures of Gaussians via Systems of Polynomial Inequalities Jerry Li, Ludwig Schmidt

ICML 2017 ZipML: Training Linear Models with End-to-End Low Precision, and a Little Bit of Deep Learning Hantian Zhang, Jerry Li, Kaan Kara, Dan Alistarh, Ji Liu, Ce Zhang

ICML 2016 Fast Algorithms for Segmented Regression Jayadev Acharya, Ilias Diakonikolas, Jerry Li, Ludwig Schmidt

UAI 2013 Lower Bounds for Exact Model Counting and Applications in Probabilistic Databases Paul Beame, Jerry Li, Sudeepa Roy, Dan Suciu