Zhiwei Steven Wu

According to our database1, Zhiwei Steven Wu authored at least 23 papers between 2014 and 2019.

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Bibliography

2019
An Empirical Study of Rich Subgroup Fairness for Machine Learning.
Proceedings of the Conference on Fairness, Accountability, and Transparency, 2019

2018
Strategic Classification from Revealed Preferences.
Proceedings of the 2018 ACM Conference on Economics and Computation, 2018

A Smoothed Analysis of the Greedy Algorithm for the Linear Contextual Bandit Problem.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Competing Bandits: Learning Under Competition.
Proceedings of the 9th Innovations in Theoretical Computer Science Conference, 2018

Semiparametric Contextual Bandits.
Proceedings of the 35th International Conference on Machine Learning, 2018

Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness.
Proceedings of the 35th International Conference on Machine Learning, 2018

The Externalities of Exploration and How Data Diversity Helps Exploitation.
Proceedings of the Conference On Learning Theory, 2018

2017
Multidimensional Dynamic Pricing for Welfare Maximization.
Proceedings of the 2017 ACM Conference on Economics and Computation, 2017

Fairness Incentives for Myopic Agents.
Proceedings of the 2017 ACM Conference on Economics and Computation, 2017

Meritocratic Fairness for Cross-Population Selection.
Proceedings of the 34th International Conference on Machine Learning, 2017

Predicting with Distributions.
Proceedings of the 30th Conference on Learning Theory, 2017

2016
Watch and learn: optimizing from revealed preferences feedback.
Proceedings of the 48th Annual ACM SIGACT Symposium on Theory of Computing, 2016

Jointly Private Convex Programming.
Proceedings of the Twenty-Seventh Annual ACM-SIAM Symposium on Discrete Algorithms, 2016

Bayesian Exploration: Incentivizing Exploration in Bayesian Games.
Proceedings of the 2016 ACM Conference on Economics and Computation, 2016

Logarithmic Query Complexity for Approximate Nash Computation in Large Games.
Proceedings of the Algorithmic Game Theory - 9th International Symposium, 2016

Coordination Complexity: Small Information Coordinating Large Populations.
Proceedings of the 2016 ACM Conference on Innovations in Theoretical Computer Science, 2016

Adaptive Learning with Robust Generalization Guarantees.
Proceedings of the 29th Conference on Learning Theory, 2016

2015
Privacy and Truthful Equilibrium Selection for Aggregative Games.
Proceedings of the Web and Internet Economics - 11th International Conference, 2015

Approximately Stable, School Optimal, and Student-Truthful Many-to-One Matchings (via Differential Privacy).
Proceedings of the Twenty-Sixth Annual ACM-SIAM Symposium on Discrete Algorithms, 2015

Inducing Approximately Optimal Flow Using Truthful Mediators.
Proceedings of the Sixteenth ACM Conference on Economics and Computation, 2015

Accuracy for Sale: Aggregating Data with a Variance Constraint.
Proceedings of the 2015 Conference on Innovations in Theoretical Computer Science, 2015

2014
Private matchings and allocations.
Proceedings of the Symposium on Theory of Computing, 2014

Dual Query: Practical Private Query Release for High Dimensional Data.
Proceedings of the 31th International Conference on Machine Learning, 2014


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