← Authors

Jerry Li

44 papers · 2016–2025 · 7 conferences · across top CS/AI conferences

Achievements

🐝 Cross-Pollinator (13) 🐣 Hot Topic Early Bird 🌈 Renaissance Researcher (7) πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (50) 🌍 Conference Polyglot (7) πŸƒ Academic Marathon (9) 🧭 Keyword Pioneer πŸ”¬ Deep Specialist (10) πŸ† Keyword Champion (4) πŸ—ƒοΈ Keyword Collector (158) ⚑ Prolific Year (6) πŸ’Ž Century Club (44) πŸ”₯ Unstoppable (10) πŸ“ˆ Trend Setter ❓ The Questioner

Conferences

NIPS (17) COLT (12) ICML (7) ICLR (5) CORL (1) EMNLP (1) ICCV (1)

Top co-authors

Sitan Chen (7) Kevin Tian (7) Ilias Diakonikolas (6) Ludwig Schmidt (5) Gautam Kamath (4) Arun Jambulapati (4) Dan Alistarh (4) Aaron Sidford (3) Yuanzhi Li (3) Ankur Moitra (3)

Research topics

Statistics (1)

Keywords

mean estimation (5) robust statistics (4) robust estimation (4) high-dimensional statistics (4) sample complexity (4) adversarial corruption (4) adversarial robustness (3) outlier detection (3) gradient descent (3) covariance estimation (3) neural network (3) certified robustness (2) statistical query (2) distribution learning (2) distributed optimization (2) stochastic gradient descent (2) computational complexity (2) distributed learning (2) semidefinite programming (2) density estimation (2)

Papers

Predicting quantum channels over general product distributions COLT 2025
BEVCalib: LiDAR-Camera Calibration via Geometry-Guided Bird’s-Eye View Representation CORL 2025
S4S: Solving for a Fast Diffusion Model Solver ICML 2025
Semi-Random Matrix Completion via Flow-Based Adaptive Reweighting NIPS 2024
Black-Box k-to-1-PCA Reductions: Theory and Applications COLT 2024
KITAB: Evaluating LLMs on Constraint Satisfaction for Information Retrieval ICLR 2024
Automatic Prompt Optimization with β€œGradient Descent” and Beam Search EMNLP 2023
Sampling is as easy as learning the score: theory for diffusion models with minimal data assumptions ICLR 2023
Semi-Random Sparse Recovery in Nearly-Linear Time COLT 2023
Structured Semidefinite Programming for Recovering Structured Preconditioners NIPS 2023
REAP: A Large-Scale Realistic Adversarial Patch Benchmark ICCV 2023
The Price of Tolerance in Distribution Testing COLT 2022
Minimax Optimality (Probably) Doesn't Imply Distribution Learning for GANs ICLR 2022
Learning (Very) Simple Generative Models Is Hard NIPS 2022
Robust Model Selection and Nearly-Proper Learning for GMMs NIPS 2022
Toward Instance-Optimal State Certification With Incoherent Measurements COLT 2022
Byzantine-Resilient Non-Convex Stochastic Gradient Descent ICLR 2021
Robust Regression Revisited: Acceleration and Improved Estimation Rates NIPS 2021
List-Decodable Mean Estimation in Nearly-PCA Time NIPS 2021
Statistical Query Algorithms and Low Degree Tests Are Almost Equivalent COLT 2021
Aligning AI With Shared Human Values ICLR 2021
Robust Gaussian Covariance Estimation in Nearly-Matrix Multiplication Time NIPS 2020
Robust and Heavy-Tailed Mean Estimation Made Simple, via Regret Minimization NIPS 2020
RL Unplugged: A Suite of Benchmarks for Offline Reinforcement Learning NIPS 2020
Learning Structured Distributions From Untrusted Batches: Faster and Simpler NIPS 2020
Randomized Smoothing of All Shapes and Sizes ICML 2020
Robust Sub-Gaussian Principal Component Analysis and Width-Independent Schatten Packing NIPS 2020
Sever: A Robust Meta-Algorithm for Stochastic Optimization ICML 2019
Privately Learning High-Dimensional Distributions COLT 2019
On Mean Estimation for General Norms with Statistical Queries COLT 2019
How Hard is Robust Mean Estimation? COLT 2019
Quantum Entropy Scoring for Fast Robust Mean Estimation and Improved Outlier Detection NIPS 2019
Provably Robust Deep Learning via Adversarially Trained Smoothed Classifiers NIPS 2019
Fast and Sample Near-Optimal Algorithms for Learning Multidimensional Histograms COLT 2018
Byzantine Stochastic Gradient Descent NIPS 2018
Spectral Signatures in Backdoor Attacks NIPS 2018
On the Limitations of First-Order Approximation in GAN Dynamics ICML 2018
Computationally Efficient Robust Sparse Estimation in High Dimensions COLT 2017
Being Robust (in High Dimensions) Can Be Practical ICML 2017
ZipML: Training Linear Models with End-to-End Low Precision, and a Little Bit of Deep Learning ICML 2017
Robust and Proper Learning for Mixtures of Gaussians via Systems of Polynomial Inequalities COLT 2017
QSGD: Communication-Efficient SGD via Gradient Quantization and Encoding NIPS 2017
Communication-Efficient Distributed Learning of Discrete Distributions NIPS 2017
Fast Algorithms for Segmented Regression ICML 2016