Eric Zhao

Affiliations:
  • University of California Berkeley, CA, USA
  • Salesforce Research, Palo Alto, CA, USA


According to our database1, Eric Zhao authored at least 12 papers between 2021 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Learning Variational Inequalities from Data: Fast Generalization Rates under Strong Monotonicity.
CoRR, 2024

Learning With Multi-Group Guarantees For Clusterable Subpopulations.
CoRR, 2024

Algorithmic Content Selection and the Impact of User Disengagement.
CoRR, 2024

Truthfulness of Calibration Measures.
CoRR, 2024

Stacking as Accelerated Gradient Descent.
CoRR, 2024

2023
The Sample Complexity of Multi-Distribution Learning for VC Classes.
CoRR, 2023

A Unifying Perspective on Multi-Calibration: Unleashing Game Dynamics for Multi-Objective Learning.
CoRR, 2023

A Unifying Perspective on Multi-Calibration: Game Dynamics for Multi-Objective Learning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Open Problem: The Sample Complexity of Multi-Distribution Learning for VC Classes.
Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

Learning to Play General-Sum Games against Multiple Boundedly Rational Agents.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
On-Demand Sampling: Learning Optimally from Multiple Distributions.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021
ERMAS: Becoming Robust to Reward Function Sim-to-Real Gaps in Multi-Agent Simulations.
CoRR, 2021


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