5 citations · 16 across the 8 of their papers we have counts for
8 papers
Collaboratively Learning Linear Models with Structured Missing Data
Chen Cheng, Gary Cheng, John Duchi
We study the problem of collaboratively learning least squares estimates for agents. Each agent observes a different subset of the features$\unicode{x2013}$e.g., containing dat…
Causal Inference out of Control: Estimating the Steerability of Consumption
Gary Cheng, Moritz Hardt, Celestine Mendler-Dünner
Regulators and academics are increasingly interested in the causal effect that algorithmic actions of a digital platform have on consumption. We introduce a general causal inferenc…
Dual Multi-scale Mean Teacher Network for Semi-supervised Infection Segmentation in Chest CT Volume for COVID-19
Liansheng Wang, Jiacheng Wang, Lei Zhu +6
Automated detecting lung infections from computed tomography (CT) data plays an important role for combating COVID-19. However, there are still some challenges for developing AI sy…
Private optimization in the interpolation regime: faster rates and hardness results
Hilal Asi, Karan Chadha, Gary Cheng +1
In non-private stochastic convex optimization, stochastic gradient methods converge much faster on interpolation problems -- problems where there exists a solution that simultaneou…
Approximate Function Evaluation via Multi-Armed Bandits
Tavor Z. Baharav, Gary Cheng, Mert Pilanci +1
We study the problem of estimating the value of a known smooth function at an unknown point , where each component can be sampled via a noi…
Federated Asymptotics: a model to compare federated learning algorithms
Gary Cheng, Karan Chadha, John Duchi
We propose an asymptotic framework to analyze the performance of (personalized) federated learning algorithms. In this new framework, we formulate federated learning as a multi-cri…