48 citations · 181 across the 57 of their papers we have counts for
4 papers · 1 filter
Synthetic Data: Opening the data floodgates to enable faster, more directed development of machine learning methods
James Jordon, Alan Wilson, Mihaela van der Schaar
Many ground-breaking advancements in machine learning can be attributed to the availability of a large volume of rich data. Unfortunately, many large-scale datasets are highly sens…
Estimating Structural Target Functions using Machine Learning and Influence Functions
Alicia Curth, Ahmed M. Alaa, Mihaela van der Schaar
We aim to construct a class of learning algorithms that are of practical value to applied researchers in fields such as biostatistics, epidemiology and econometrics, where the need…
Learning "What-if" Explanations for Sequential Decision-Making
Ioana Bica, Daniel Jarrett, Alihan Hüyük +1
Building interpretable parameterizations of real-world decision-making on the basis of demonstrated behavior -- i.e. trajectories of observations and actions made by an expert maxi…
Contextual Constrained Learning for Dose-Finding Clinical Trials
Hyun-Suk Lee, Cong Shen, James Jordon +1
Clinical trials in the medical domain are constrained by budgets. The number of patients that can be recruited is therefore limited. When a patient population is heterogeneous, thi…