Alexander Wei - RankMe

27 papers A* 11Journal 13Unranked 2

Year	Rank	Type	Title / Venue / Authors
2024	A*	`conf`	Covert Malicious Finetuning: Challenges in Safeguarding LLM Adaptation. ICML Danny Halawi, Alexander Wei, Eric Wallace, Tony Tong Wang, Nika Haghtalab, Jacob Steinhardt
2024	J	`jnl`	Covert Malicious Finetuning: Challenges in Safeguarding LLM Adaptation. CoRR Danny Halawi, Alexander Wei, Eric Wallace, Tony T. Wang, Nika Haghtalab, Jacob Steinhardt
2023	J	`jnl`	Designing Approximately Optimal Search on Matching Platforms. Manag. Sci. Nicole Immorlica, Brendan Lucier, Vahideh H. Manshadi, Alexander Wei
2023	A*	`conf`	Jailbroken: How Does LLM Safety Training Fail? NeurIPS Alexander Wei, Nika Haghtalab, Jacob Steinhardt
2023	J	`jnl`	Jailbroken: How Does LLM Safety Training Fail? CoRR Alexander Wei, Nika Haghtalab, Jacob Steinhardt
2023	J	`jnl`	Learning Equilibria in Matching Markets with Bandit Feedback. J. ACM Meena Jagadeesan, Alexander Wei, Yixin Wang, Michael I. Jordan, Jacob Steinhardt
2023	—	`—`	Learning and Decision-Making in Complex Environments Alexander Wei
2022	A*	`conf`	Learning in Stackelberg Games with Non-myopic Agents. EC Nika Haghtalab, Thodoris Lykouris, Sloan Nietert, Alexander Wei
2022	A*	`conf`	More Than a Toy: Random Matrix Models Predict How Real-World Neural Representations Generalize. ICML Alexander Wei, Wei Hu, Jacob Steinhardt
2022	J	`jnl`	More Than a Toy: Random Matrix Models Predict How Real-World Neural Representations Generalize. CoRR Alexander Wei, Wei Hu, Jacob Steinhardt
2022	J	`jnl`	Optimal Las Vegas Approximate Near Neighbors in ACM Trans. Algorithms Alexander Wei
2022	A*	`conf`	Predicting Out-of-Distribution Error with the Projection Norm. ICML Yaodong Yu, Zitong Yang, Alexander Wei, Yi Ma, Jacob Steinhardt
2022	J	`jnl`	Predicting Out-of-Distribution Error with the Projection Norm. CoRR Yaodong Yu, Zitong Yang, Alexander Wei, Yi Ma, Jacob Steinhardt
2022	A*	`conf`	TCT: Convexifying Federated Learning using Bootstrapped Neural Tangent Kernels. NeurIPS Yaodong Yu, Alexander Wei, Sai Praneeth Karimireddy, Yi Ma, Michael I. Jordan
2022	J	`jnl`	TCT: Convexifying Federated Learning using Bootstrapped Neural Tangent Kernels. CoRR Yaodong Yu, Alexander Wei, Sai Praneeth Karimireddy, Yi Ma, Michael I. Jordan
2021	A*	`conf`	Designing Approximately Optimal Search on Matching Platforms. EC Nicole Immorlica, Brendan Lucier, Vahideh H. Manshadi, Alexander Wei
2021	J	`jnl`	Designing Approximately Optimal Search on Matching Platforms. CoRR Nicole Immorlica, Brendan Lucier, Vahideh H. Manshadi, Alexander Wei
2021	A*	`conf`	Learning Equilibria in Matching Markets from Bandit Feedback. NeurIPS Meena Jagadeesan, Alexander Wei, Yixin Wang, Michael I. Jordan, Jacob Steinhardt
2021	J	`jnl`	Learning Equilibria in Matching Markets from Bandit Feedback. CoRR Meena Jagadeesan, Alexander Wei, Yixin Wang, Michael I. Jordan, Jacob Steinhardt
2020	—	`conf`	Better and Simpler Learning-Augmented Online Caching. APPROX-RANDOM Alexander Wei
2020	J	`jnl`	Better and Simpler Learning-Augmented Online Caching. CoRR Alexander Wei
2020	A*	`conf`	Optimal Robustness-Consistency Trade-offs for Learning-Augmented Online Algorithms. NeurIPS Alexander Wei, Fred Zhang
2020	J	`jnl`	Optimal Robustness-Consistency Trade-offs for Learning-Augmented Online Algorithms. CoRR Alexander Wei, Fred Zhang
2019	A*	`conf`	Allocation for Social Good: Auditing Mechanisms for Utility Maximization. EC Taylor Lundy, Alexander Wei, Hu Fu, Scott Duke Kominers, Kevin Leyton-Brown
2019	A*	`conf`	Optimal Las Vegas Approximate Near Neighbors in ℓp. SODA Alexander Wei
2018	J	`jnl`	Optimal Las Vegas Approximate Near Neighbors in 𝓁 CoRR Alexander Wei
2018	—	`conf`	Varying the Number of Signals in Matching Markets. WINE Meena Jagadeesan, Alexander Wei