Gary Cheng - RankMe

14 papers A* 5A 2Journal 6Unranked 1

Year	Rank	Type	Title / Venue / Authors
2024	A*	`conf`	Causal Inference out of Control: Estimating Performativity without Treatment Randomization. ICML Gary Cheng, Moritz Hardt, Celestine Mendler-Dünner
2023	J	`jnl`	Causal Inference out of Control: Estimating the Steerability of Consumption. CoRR Gary Cheng, Moritz Hardt, Celestine Mendler-Dünner
2023	A*	`conf`	Collaboratively Learning Linear Models with Structured Missing Data. NeurIPS Chen Cheng, Gary Cheng, John C. Duchi
2023	J	`jnl`	Collaboratively Learning Linear Models with Structured Missing Data. CoRR Chen Cheng, Gary Cheng, John C. Duchi
2023	A	`conf`	Federated Asymptotics: a model to compare federated learning algorithms. AISTATS Gary Cheng, Karan N. Chadha, John C. Duchi
2022	A*	`conf`	Accelerated, Optimal and Parallel: Some results on model-based stochastic optimization. ICML Karan N. Chadha, Gary Cheng, John C. Duchi
2022	A	`conf`	Approximate Function Evaluation via Multi-Armed Bandits. AISTATS Tavor Z. Baharav, Gary Cheng, Mert Pilanci, David Tse
2022	J	`jnl`	Approximate Function Evaluation via Multi-Armed Bandits. CoRR Tavor Z. Baharav, Gary Cheng, Mert Pilanci, David Tse
2022	—	`conf`	Does Federated Dropout actually work? CVPR Workshops Gary Cheng, Zachary Charles, Zachary Garrett, Keith Rush
2022	A*	`conf`	Private optimization in the interpolation regime: faster rates and hardness results. ICML Hilal Asi, Karan N. Chadha, Gary Cheng, John C. Duchi
2022	J	`jnl`	Private optimization in the interpolation regime: faster rates and hardness results. CoRR Hilal Asi, Karan N. Chadha, Gary Cheng, John C. Duchi
2021	J	`jnl`	Accelerated, Optimal, and Parallel: Some Results on Model-Based Stochastic Optimization. CoRR Karan N. Chadha, Gary Cheng, John C. Duchi
2021	J	`jnl`	Fine-tuning is Fine in Federated Learning. CoRR Gary Cheng, Karan N. Chadha, John C. Duchi
2020	A*	`conf`	Minibatch Stochastic Approximate Proximal Point Methods. NeurIPS Hilal Asi, Karan N. Chadha, Gary Cheng, John C. Duchi