Joshua R. Wang

Orcid: 0009-0004-0770-0621

Affiliations:
  • Google Research, Mountain View, CA, USA
  • Stanford University, Department of Computer Science, CA, USA


According to our database1, Joshua R. Wang authored at least 31 papers between 2013 and 2024.

Collaborative distances:

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2024
Contracting with a Learning Agent.
CoRR, 2024

Prior-Free Mechanism with Welfare Guarantees.
Proceedings of the ACM on Web Conference 2024, 2024

2023
Online Learning via Offline Greedy Algorithms: Applications in Market Design and Optimization.
Manag. Sci., July, 2023

Approximation Bounds for Hierarchical Clustering: Average Linkage, Bisecting K-means, and Local Search.
J. Mach. Learn. Res., 2023

New Tools for Peak Memory Scheduling.
CoRR, 2023

The Power of Menus in Contract Design.
Proceedings of the 24th ACM Conference on Economics and Computation, 2023

Optimal No-Regret Learning for One-Sided Lipschitz Functions.
Proceedings of the International Conference on Machine Learning, 2023

Efficient Caching with Reserves via Marking.
Proceedings of the 50th International Colloquium on Automata, Languages, and Programming, 2023

2022
Scheduling with Communication Delay in Near-Linear Time.
Proceedings of the 39th International Symposium on Theoretical Aspects of Computer Science, 2022

Caching with Reserves.
Proceedings of the Approximation, 2022

2021
Contracts under Moral Hazard and Adverse Selection.
Proceedings of the EC '21: The 22nd ACM Conference on Economics and Computation, 2021

Margin-Independent Online Multiclass Learning via Convex Geometry.
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.
J. Mach. Learn. Res., 2020

2019
Minimizing Regret with Multiple Reserves.
ACM Trans. Economics and Comput., 2019

Efficient Rematerialization for Deep Networks.
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.
Proceedings of the 36th International Conference on Machine Learning, 2019

On the Computational Power of Online Gradient Descent.
Proceedings of the Conference on Learning Theory, 2019

2018
Theoretical models for practical problems: dynamic data structures, hierarchical clustering, and modern parallel computing.
PhD thesis, 2018

Shuffles and Circuits (On Lower Bounds for Modern Parallel Computation).
J. ACM, 2018

An Optimal Algorithm for Online Unconstrained Submodular Maximization.
CoRR, 2018

An Optimal Learning Algorithm for Online Unconstrained Submodular Maximization.
Proceedings of the Conference On Learning Theory, 2018

2017
Cell-Probe Lower Bounds from Online Communication Complexity.
Electron. Colloquium Comput. Complex., 2017

2016
Exact Algorithms and Strong Exponential Time Hypothesis.
Encyclopedia of Algorithms, 2016

Deterministic Time-Space Tradeoffs for k-SUM.
CoRR, 2016

Approximation and Fixed Parameter Subquadratic Algorithms for Radius and Diameter in Sparse Graphs.
Proceedings of the Twenty-Seventh Annual ACM-SIAM Symposium on Discrete Algorithms, 2016

Deterministic Time-Space Trade-Offs for k-SUM.
Proceedings of the 43rd International Colloquium on Automata, Languages, and Programming, 2016

The Complexity of the k-means Method.
Proceedings of the 24th Annual European Symposium on Algorithms, 2016

2015
Approximation and Fixed Parameter Subquadratic Algorithms for Radius and Diameter.
CoRR, 2015

Finding Four-Node Subgraphs in Triangle Time.
Proceedings of the Twenty-Sixth Annual ACM-SIAM Symposium on Discrete Algorithms, 2015

2014
Space-Efficient Randomized Algorithms for K-SUM.
Proceedings of the Algorithms - ESA 2014, 2014

2013
Space-Efficient Las Vegas Algorithms for K-SUM
CoRR, 2013


  Loading...