Zhiwei Steven Wu
21 papers · 2014–2025 · 4 conferences · across top CS/AI conferences
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Academic Marathon
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Conferences
ICML (7)
NIPS (7)
COLT (6)
AAAI (1)
Top co-authors
Research topics
Keywords
differential privacy
(5)
online learning
(3)
contextual bandit
(3)
regret bound
(3)
sample complexity
(3)
regret minimization
(2)
pac learning
(2)
greedy algorithm
(2)
distribution shift
(2)
robust learning
(2)
imitation learning
(1)
out-of-distribution generalization
(1)
machine unlearning
(1)
covariate shift
(1)
regret analysis
(1)
online convex optimization
(1)
algorithmic fairness
(1)
classification noise
(1)
agnostic learning
(1)
bayesian inference
(1)
Papers
Time-Uniform Self-Normalized Concentration for Vector-Valued Processes (Extended Abstract)
COLT 2025
Orthogonal Causal Calibration (Extended Abstract)
COLT 2025
Regret Minimization in Stackelberg Games with Side Information
NIPS 2024
Multi-Agent Imitation Learning: Value is Easy, Regret is Hard
NIPS 2024
Bridging Multicalibration and Out-of-distribution Generalization Beyond Covariate Shift
NIPS 2024
Reconstruction Attacks on Machine Unlearning: Simple Models are Vulnerable
NIPS 2024
Oracle-Efficient Differentially Private Learning with Public Data
NIPS 2024
On the Benefits of Public Representations for Private Transfer Learning under Distribution Shift
NIPS 2024
Bandit Data-Driven Optimization for Crowdsourcing Food Rescue Platforms
AAAI 2022
Locally Private Hypothesis Selection
COLT 2020
Orthogonal Random Forest for Causal Inference
ICML 2019
Locally Private Bayesian Inference for Count Models
ICML 2019
Fair Regression: Quantitative Definitions and Reduction-Based Algorithms
ICML 2019
The Externalities of Exploration and How Data Diversity Helps Exploitation
COLT 2018
A Smoothed Analysis of the Greedy Algorithm for the Linear Contextual Bandit Problem
NIPS 2018
Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness
ICML 2018
Semiparametric Contextual Bandits
ICML 2018
Meritocratic Fairness for Cross-Population Selection
ICML 2017
Predicting with Distributions
COLT 2017
Adaptive Learning with Robust Generalization Guarantees
COLT 2016
Dual Query: Practical Private Query Release for High Dimensional Data
ICML 2014