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Found 6 papers, 4 papers with code
Human Strategic Steering Improves Performance of Interactive Optimization
To verify this hypothesis, that humans steer and are able to improve performance by steering, we designed a function optimization task where a human and an optimization algorithm collaborate to find the maximum of a 1-dimensional function.
Interactive AI with a Theory of Mind
Understanding each other is the key to success in collaboration.
Machine Teaching of Active Sequential Learners
We formulate this sequential teaching problem, which current techniques in machine teaching do not address, as a Markov decision process, with the dynamics nesting a model of the learner and the actions being the teacher's responses.
User Modelling for Avoiding Overfitting in Interactive Knowledge Elicitation for Prediction
In human-in-the-loop machine learning, the user provides information beyond that in the training data.
Improving drug sensitivity predictions in precision medicine through active expert knowledge elicitation
Predicting the efficacy of a drug for a given individual, using high-dimensional genomic measurements, is at the core of precision medicine.
Knowledge Elicitation via Sequential Probabilistic Inference for High-Dimensional Prediction
Prediction in a small-sized sample with a large number of covariates, the "small n, large p" problem, is challenging.
