Steven Z. Wu
25 papers · 2016–2023 · 1 conference · across top CS/AI conferences
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π Interdisciplinary Bridge πΊοΈ Taxonomy Completionist (38) π Academic Marathon (7) π Renaissance Researcher (6) π§ Keyword Pioneer
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(6)
π§
Keyword Pioneer
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Conference Loyalist
(25)
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Deep Specialist
(10)
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Prolific Year
(7)
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Keyword Collector
(123)
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Unstoppable
(5)
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Century Club
(25)
Conferences
NIPS (25)
Top co-authors
Research topics
Keywords
differential privacy
(9)
online learning
(6)
imitation learning
(2)
stochastic gradient descent
(2)
pac learning
(2)
federated learning
(2)
multi-armed bandit
(2)
multi-task 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
Scalable Membership Inference Attacks via Quantile Regression
NIPS 2023
Strategic Apple Tasting
NIPS 2023
Adaptive Principal Component Regression with Applications to Panel Data
NIPS 2023
Meta-Learning Adversarial Bandit Algorithms
NIPS 2023
On the Sublinear Regret of GP-UCB
NIPS 2023
Adaptive Privacy Composition for Accuracy-first Mechanisms
NIPS 2023
Learning Shared Safety Constraints from Multi-task Demonstrations
NIPS 2023
Minimax Optimal Online Imitation Learning via Replay Estimation
NIPS 2022
On Privacy and Personalization in Cross-Silo Federated Learning
NIPS 2022
Bayesian Persuasion for Algorithmic Recourse
NIPS 2022
Brownian Noise Reduction: Maximizing Privacy Subject to Accuracy Constraints
NIPS 2022
Sequence Model Imitation Learning with Unobserved Contexts
NIPS 2022
Private Synthetic Data for Multitask Learning and Marginal Queries
NIPS 2022
Incentivizing Combinatorial Bandit Exploration
NIPS 2022
Iterative Methods for Private Synthetic Data: Unifying Framework and New Methods
NIPS 2021
Stateful Strategic Regression
NIPS 2021
Distributed Training with Heterogeneous Data: Bridging Median- and Mean-Based Algorithms
NIPS 2020
Metric-Free Individual Fairness in Online Learning
NIPS 2020
Understanding Gradient Clipping in Private SGD: A Geometric Perspective
NIPS 2020
Locally Private Gaussian Estimation
NIPS 2019
Random Quadratic Forms with Dependence: Applications to Restricted Isometry and Beyond
NIPS 2019
Equal Opportunity in Online Classification with Partial Feedback
NIPS 2019
Private Hypothesis Selection
NIPS 2019
Accuracy First: Selecting a Differential Privacy Level for Accuracy Constrained ERM
NIPS 2017
Learning from Rational Behavior: Predicting Solutions to Unknown Linear Programs
NIPS 2016