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ORCIDEric Zhao 0003
Person information
- affiliation: University of California Berkeley, CA, USA
- affiliation: Salesforce Research, Palo Alto, CA, USA
Other persons with the same name
- Yihong Eric Zhao (aka: Yihong Zhao 0002, Eric Zhao 0001) — JD.com, Beijing, China (and 1 more)
- Eric Zhao 0002
![[0000-0002-9595-0150]](https://dblp.org/img/orcid-mark.12x12.png "0000-0002-9595-0150")
— California Institute of Technology, Pasadena, CA, USA - Eric Zhao 0004 — Azanda Network Devices, Inc., Sunnyvale, CA, USA
- Eric Zhao 0005 — Carnegie Mellon University, School of Design, Pittsburgh, PA, USA
- Eric Zhao 0006 — University of Michigan, Ann Arbor, MI, USA
- Eric Zhao 0007 — University of Pennsylvania, PA, USA
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2020 – today
- 2024
[i6]Naman Agarwal, Pranjal Awasthi, Satyen Kale, Eric Zhao:
Stacking as Accelerated Gradient Descent. CoRR abs/2403.04978 (2024)- [i5]Nika Haghtalab, Mingda Qiao, Kunhe Yang, Eric Zhao:
Truthfulness of Calibration Measures. CoRR abs/2407.13979 (2024) - 2023
- [c4]Eric Zhao, Alexander R. Trott, Caiming Xiong, Stephan Zheng:
Learning to Play General-Sum Games against Multiple Boundedly Rational Agents. AAAI 2023: 11781-11789 - [c3]Pranjal Awasthi, Nika Haghtalab, Eric Zhao:
Open Problem: The Sample Complexity of Multi-Distribution Learning for VC Classes. COLT 2023: 5943-5949 - [c2]Nika Haghtalab, Michael I. Jordan, Eric Zhao:
A Unifying Perspective on Multi-Calibration: Game Dynamics for Multi-Objective Learning. NeurIPS 2023 - [i4]Nika Haghtalab, Michael I. Jordan, Eric Zhao:
A Unifying Perspective on Multi-Calibration: Unleashing Game Dynamics for Multi-Objective Learning. CoRR abs/2302.10863 (2023) - [i3]Pranjal Awasthi, Nika Haghtalab, Eric Zhao:
The Sample Complexity of Multi-Distribution Learning for VC Classes. CoRR abs/2307.12135 (2023) - 2022
- [c1]Nika Haghtalab, Michael I. Jordan, Eric Zhao:
On-Demand Sampling: Learning Optimally from Multiple Distributions. NeurIPS 2022 - [i2]Nika Haghtalab, Michael I. Jordan, Eric Zhao:
On-Demand Sampling: Learning Optimally from Multiple Distributions. CoRR abs/2210.12529 (2022) - 2021
- [i1]Eric Zhao, Alexander R. Trott, Caiming Xiong, Stephan Zheng:
ERMAS: Becoming Robust to Reward Function Sim-to-Real Gaps in Multi-Agent Simulations. CoRR abs/2106.05492 (2021)
Coauthor Index
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