Jerry Li
45 papers · 2016–2026 · 8 conferences · across top CS/AI conferences
Achievements
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π Academic Marathon (9) π Interdisciplinary Bridge π§ Keyword Pioneer π Conference Polyglot (7) π£ Hot Topic Early Bird
π
Conference Polyglot
(7)
π
Academic Marathon
(9)
π§
Keyword Pioneer
π¬
Deep Specialist
(10)
π
Keyword Champion
(4)
ποΈ
Keyword Collector
(158)
β‘
Prolific Year
(6)
π
Century Club
(44)
π₯
Unstoppable
(10)
π
Trend Setter
β
The Questioner
Conferences
NIPS (17)
COLT (12)
ICML (7)
ICLR (5)
ACL (1)
CORL (1)
EMNLP (1)
ICCV (1)
Top co-authors
Research topics
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
Are LLMs Reliable Rankers? Rank Manipulation via Two-Stage Token Optimization
ACL 2026
BEVCalib: LiDAR-Camera Calibration via Geometry-Guided Birdβs-Eye View Representation
CORL 2025
Predicting quantum channels over general product distributions
COLT 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 βGradient Descentβ and Beam Search
EMNLP 2023
Sampling is as easy as learning the score: theory for diffusion models with minimal data assumptions
ICLR 2023
REAP: A Large-Scale Realistic Adversarial Patch Benchmark
ICCV 2023
Structured Semidefinite Programming for Recovering Structured Preconditioners
NIPS 2023
Semi-Random Sparse Recovery in Nearly-Linear Time
COLT 2023
Minimax Optimality (Probably) Doesn't Imply Distribution Learning for GANs
ICLR 2022
Robust Model Selection and Nearly-Proper Learning for GMMs
NIPS 2022
Learning (Very) Simple Generative Models Is Hard
NIPS 2022
The Price of Tolerance in Distribution Testing
COLT 2022
Toward Instance-Optimal State Certification With Incoherent Measurements
COLT 2022
Statistical Query Algorithms and Low Degree Tests Are Almost Equivalent
COLT 2021
Robust Regression Revisited: Acceleration and Improved Estimation Rates
NIPS 2021
List-Decodable Mean Estimation in Nearly-PCA Time
NIPS 2021
Byzantine-Resilient Non-Convex Stochastic Gradient Descent
ICLR 2021
Aligning AI With Shared Human Values
ICLR 2021
Robust Sub-Gaussian Principal Component Analysis and Width-Independent Schatten Packing
NIPS 2020
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
On Mean Estimation for General Norms with Statistical Queries
COLT 2019
Provably Robust Deep Learning via Adversarially Trained Smoothed Classifiers
NIPS 2019
Privately Learning High-Dimensional Distributions
COLT 2019
Quantum Entropy Scoring for Fast Robust Mean Estimation and Improved Outlier Detection
NIPS 2019
How Hard is Robust Mean Estimation?
COLT 2019
Sever: A Robust Meta-Algorithm for Stochastic Optimization
ICML 2019
On the Limitations of First-Order Approximation in GAN Dynamics
ICML 2018
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
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
QSGD: Communication-Efficient SGD via Gradient Quantization and Encoding
NIPS 2017
Robust and Proper Learning for Mixtures of Gaussians via Systems of Polynomial Inequalities
COLT 2017
Computationally Efficient Robust Sparse Estimation in High Dimensions
COLT 2017
Communication-Efficient Distributed Learning of Discrete Distributions
NIPS 2017
Fast Algorithms for Segmented Regression
ICML 2016