Donald Geman — accepted AI-conference papers

2024

Performance Bounds for Active Binary Testing with Information Maximization

Aditya Chattopadhyay, Benjamin David Haeffele, Rene Vidal, Donald Geman

ICML 2024poster

In many applications like experimental design, group testing, and medical diagnosis, the state of a random variable $Y$ is revealed by successively observing the outcomes of binary tests about $Y$. New tests are selected adaptively based on the history of outcomes observed so far. If the number of s…

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2023

Variational Information Pursuit for Interpretable Predictions

Aditya Chattopadhyay, Kwan Ho Ryan Chan, Benjamin David Haeffele, Donald Geman, Rene Vidal

ICLR 2023poster

There is a growing interest in the machine learning community in developing predictive algorithms that are interpretable by design. To this end, recent work proposes to sequentially ask interpretable queries about data until a high confidence prediction can be made based on the answers obtained (the…

Cited by 30 Source ↗PDF ↗code ↗Scholar ↗