ERMAS: Becoming Robust to Reward Function Sim-to-Real Gaps in Multi-Agent Simulations. - Eric Zhao 003; Alexander R. Trott; Caiming Xiong; Stephan Zheng (CoRR, 2021)

On-Demand Sampling: Learning Optimally from Multiple Distributions. - Nika Haghtalab; Michael I. Jordan; Eric Zhao 003 (NeurIPS, 2022)

Learning to Play General-Sum Games against Multiple Boundedly Rational Agents. - Eric Zhao 003; Alexander R. Trott; Caiming Xiong; Stephan Zheng (AAAI, 2023)

Open Problem: The Sample Complexity of Multi-Distribution Learning for VC Classes. - Pranjal Awasthi; Nika Haghtalab; Eric Zhao 003 (COLT, 2023)

A Unifying Perspective on Multi-Calibration: Game Dynamics for Multi-Objective Learning. - Nika Haghtalab; Michael I. Jordan; Eric Zhao 003 (NeurIPS, 2023)

A Unifying Perspective on Multi-Calibration: Unleashing Game Dynamics for Multi-Objective Learning. - Nika Haghtalab; Michael I. Jordan; Eric Zhao 003 (CoRR, 2023)

The Sample Complexity of Multi-Distribution Learning for VC Classes. - Pranjal Awasthi; Nika Haghtalab; Eric Zhao 003 (CoRR, 2023)

Semantic Routing via Autoregressive Modeling. - Eric Zhao 003; Pranjal Awasthi; Zhengdao Chen; Sreenivas Gollapudi; Daniel Delling (NeurIPS, 2024)

Truthfulness of Calibration Measures. - Nika Haghtalab; Mingda Qiao; Kunhe Yang; Eric Zhao 003 (NeurIPS, 2024)

Stacking as Accelerated Gradient Descent. - Naman Agarwal; Pranjal Awasthi; Satyen Kale; Eric Zhao 003 (CoRR, 2024)

Algorithmic Content Selection and the Impact of User Disengagement. - Emilio Calvano; Nika Haghtalab; Ellen Vitercik; Eric Zhao 003 (CoRR, 2024)

Learning With Multi-Group Guarantees For Clusterable Subpopulations. - Jessica Dai; Nika Haghtalab; Eric Zhao 003 (CoRR, 2024)

Learning Variational Inequalities from Data: Fast Generalization Rates under Strong Monotonicity. - Eric Zhao 003; Tatjana Chavdarova; Michael I. Jordan (CoRR, 2024)

Truthfulness of Decision-Theoretic Calibration Measures. - Mingda Qiao; Eric Zhao 003 (COLT, 2025)

Sample, Scrutinize and Scale: Effective Inference-Time Search by Scaling Verification. - Eric Zhao 003; Pranjal Awasthi; Sreenivas Gollapudi (CoRR, 2025)

From Style to Facts: Mapping the Boundaries of Knowledge Injection with Finetuning. - Eric Zhao 003; Pranjal Awasthi; Nika Haghtalab (CoRR, 2025)

The Limits of Preference Data for Post-Training. - Eric Zhao 003; Jessica Dai; Pranjal Awasthi (CoRR, 2025)