Joshua R. Wang

According to our database, Joshua R. Wang authored at least 31 papers between 2013 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2024

Contracting with a Learning Agent.

Guru Guruganesh, Yoav Kolumbus, Jon Schneider, Inbal Talgam-Cohen, Emmanouil-Vasileios Vlatakis-Gkaragkounis, Joshua R. Wang, S. Matthew Weinberg

CoRR, 2024

Prior-Free Mechanism with Welfare Guarantees.

Guru Guruganesh, Jon Schneider, Joshua R. Wang

Proceedings of the ACM on Web Conference 2024, 2024

2023

Online Learning via Offline Greedy Algorithms: Applications in Market Design and Optimization.

Rad Niazadeh, Negin Golrezaei, Joshua R. Wang, Fransisca Susan, Ashwinkumar Badanidiyuru

Manag. Sci., July, 2023

Approximation Bounds for Hierarchical Clustering: Average Linkage, Bisecting K-means, and Local Search.

Benjamin Moseley, Joshua R. Wang

J. Mach. Learn. Res., 2023

New Tools for Peak Memory Scheduling.

Ce Jin, Manish Purohit, Zoya Svitkina, Erik Vee, Joshua R. Wang

CoRR, 2023

The Power of Menus in Contract Design.

Guru Guruganesh, Jon Schneider, Joshua R. Wang, Junyao Zhao

Proceedings of the 24th ACM Conference on Economics and Computation, 2023

Optimal No-Regret Learning for One-Sided Lipschitz Functions.

Paul Duetting, Guru Guruganesh, Jon Schneider, Joshua Ruizhi Wang

Proceedings of the International Conference on Machine Learning, 2023

Efficient Caching with Reserves via Marking.

Sharat Ibrahimpur, Manish Purohit, Zoya Svitkina, Erik Vee, Joshua R. Wang

Proceedings of the 50th International Colloquium on Automata, Languages, and Programming, 2023

2022

Scheduling with Communication Delay in Near-Linear Time.

Quanquan C. Liu, Manish Purohit, Zoya Svitkina, Erik Vee, Joshua R. Wang

Proceedings of the 39th International Symposium on Theoretical Aspects of Computer Science, 2022

Caching with Reserves.

Sharat Ibrahimpur, Manish Purohit, Zoya Svitkina, Erik Vee, Joshua R. Wang

Proceedings of the Approximation, 2022

2021

Contracts under Moral Hazard and Adverse Selection.

Guru Guruganesh, Jon Schneider, Joshua R. Wang

Proceedings of the EC '21: The 22nd ACM Conference on Economics and Computation, 2021

Margin-Independent Online Multiclass Learning via Convex Geometry.

Guru Guruganesh, Allen Liu, Jon Schneider, Joshua R. Wang

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Optimal Algorithms for Continuous Non-monotone Submodular and DR-Submodular Maximization.

Rad Niazadeh, Tim Roughgarden, Joshua R. Wang

J. Mach. Learn. Res., 2020

2019

Minimizing Regret with Multiple Reserves.

Tim Roughgarden, Joshua R. Wang

ACM Trans. Economics and Comput., 2019

Efficient Rematerialization for Deep Networks.

Ravi Kumar, Manish Purohit, Zoya Svitkina, Erik Vee, Joshua R. Wang

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Recursive Sketches for Modular Deep Learning.

Badih Ghazi, Rina Panigrahy, Joshua R. Wang

Proceedings of the 36th International Conference on Machine Learning, 2019

On the Computational Power of Online Gradient Descent.

Vaggos Chatziafratis, Tim Roughgarden, Joshua R. Wang

Proceedings of the Conference on Learning Theory, 2019

2018

Theoretical models for practical problems: dynamic data structures, hierarchical clustering, and modern parallel computing.

Joshua R. Wang

PhD thesis, 2018

Shuffles and Circuits (On Lower Bounds for Modern Parallel Computation).

Tim Roughgarden, Sergei Vassilvitskii, Joshua R. Wang

J. ACM, 2018

An Optimal Algorithm for Online Unconstrained Submodular Maximization.

Tim Roughgarden, Joshua R. Wang

CoRR, 2018

An Optimal Learning Algorithm for Online Unconstrained Submodular Maximization.

Tim Roughgarden, Joshua R. Wang

Proceedings of the Conference On Learning Theory, 2018

2017

Cell-Probe Lower Bounds from Online Communication Complexity.

Josh Alman, Joshua R. Wang, Huacheng Yu

Electron. Colloquium Comput. Complex., 2017

2016

Exact Algorithms and Strong Exponential Time Hypothesis.

Joshua R. Wang, Richard Ryan Williams

Encyclopedia of Algorithms, 2016

Deterministic Time-Space Tradeoffs for k-SUM.

Andrea Lincoln, Virginia Vassilevska Williams, Joshua R. Wang, R. Ryan Williams

CoRR, 2016

Approximation and Fixed Parameter Subquadratic Algorithms for Radius and Diameter in Sparse Graphs.

Amir Abboud, Virginia Vassilevska Williams, Joshua R. Wang

Proceedings of the Twenty-Seventh Annual ACM-SIAM Symposium on Discrete Algorithms, 2016

Deterministic Time-Space Trade-Offs for k-SUM.

Andrea Lincoln, Virginia Vassilevska Williams, Joshua R. Wang, R. Ryan Williams

Proceedings of the 43rd International Colloquium on Automata, Languages, and Programming, 2016

The Complexity of the k-means Method.

Tim Roughgarden, Joshua R. Wang

Proceedings of the 24th Annual European Symposium on Algorithms, 2016

2015

Approximation and Fixed Parameter Subquadratic Algorithms for Radius and Diameter.

Amir Abboud, Virginia Vassilevska Williams, Joshua R. Wang

CoRR, 2015

Finding Four-Node Subgraphs in Triangle Time.

Virginia Vassilevska Williams, Joshua R. Wang, Richard Ryan Williams, Huacheng Yu

Proceedings of the Twenty-Sixth Annual ACM-SIAM Symposium on Discrete Algorithms, 2015

2014

Space-Efficient Randomized Algorithms for K-SUM.

Joshua R. Wang

Proceedings of the Algorithms - ESA 2014, 2014

2013

Space-Efficient Las Vegas Algorithms for K-SUM

Joshua R. Wang

CoRR, 2013