Steven Z. Wu
25 papers · 2016–2023 · 1 venue · across top CS/AI venues
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Achievements
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π Interdisciplinary Bridge Β· Silver π Academic Marathon Β· Sprint π£ Hot Topic Early Bird πΊοΈ Taxonomy Completionist (36) π Conference Loyalist (25)
π¬
Deep Specialist
(10)
π
Century Club Β· Bronze
β‘
Prolific Year Β· Productive
ποΈ
Keyword Collector
(122)
π₯
Unstoppable Β· Bronze
Venues
Top co-authors
Research topics
Machine Learning
(22)
Application Areas
(12)
Optimization & Theory
(11)
Artificial Intelligence
(9)
Learning Types
(9)
Mathematics & Optimization
(7)
Core AI
(6)
Core Methods
(5)
Optimization
(5)
Security & Privacy
(4)
Reinforcement Learning
(3)
Methods
(3)
Deep Learning
(2)
Differential Privacy
(2)
Learning Paradigms
(2)
Keywords
differential privacy
(9)
online learning
(6)
multi-task learning
(3)
imitation learning
(2)
multi-armed bandit
(2)
federated learning
(2)
stochastic gradient descent
(2)
pac learning
(2)
reinforcement learning
(1)
game theory
(1)
privacy attack
(1)
model security
(1)
logistic regression
(1)
policy gradient
(1)
causal inference
(1)
distributed learning
(1)
sample complexity
(1)
sequential decision making
(1)
privacy preservation
(1)
statistical learning
(1)
Papers
Adaptive Principal Component Regression with Applications to Panel Data
NeurIPS 2023
Adaptive Privacy Composition for Accuracy-first Mechanisms
NeurIPS 2023
Learning Shared Safety Constraints from Multi-task Demonstrations
NeurIPS 2023
Meta-Learning Adversarial Bandit Algorithms
NeurIPS 2023
On the Sublinear Regret of GP-UCB
NeurIPS 2023
Scalable Membership Inference Attacks via Quantile Regression
NeurIPS 2023
Strategic Apple Tasting
NeurIPS 2023
Bayesian Persuasion for Algorithmic Recourse
NeurIPS 2022
Brownian Noise Reduction: Maximizing Privacy Subject to Accuracy Constraints
NeurIPS 2022
Incentivizing Combinatorial Bandit Exploration
NeurIPS 2022
Minimax Optimal Online Imitation Learning via Replay Estimation
NeurIPS 2022
On Privacy and Personalization in Cross-Silo Federated Learning
NeurIPS 2022
Private Synthetic Data for Multitask Learning and Marginal Queries
NeurIPS 2022
Sequence Model Imitation Learning with Unobserved Contexts
NeurIPS 2022
Iterative Methods for Private Synthetic Data: Unifying Framework and New Methods
NeurIPS 2021
Stateful Strategic Regression
NeurIPS 2021
Distributed Training with Heterogeneous Data: Bridging Median- and Mean-Based Algorithms
NeurIPS 2020
Metric-Free Individual Fairness in Online Learning
NeurIPS 2020
Understanding Gradient Clipping in Private SGD: A Geometric Perspective
NeurIPS 2020
Equal Opportunity in Online Classification with Partial Feedback
NeurIPS 2019
Locally Private Gaussian Estimation
NeurIPS 2019
Private Hypothesis Selection
NeurIPS 2019
Random Quadratic Forms with Dependence: Applications to Restricted Isometry and Beyond
NeurIPS 2019
Accuracy First: Selecting a Differential Privacy Level for Accuracy Constrained ERM
NeurIPS 2017
Learning from Rational Behavior: Predicting Solutions to Unknown Linear Programs
NeurIPS 2016