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Found 4 papers, 1 papers with code
Eliciting Model Steering Interactions from Users via Data and Visual Design Probes
In this research, we conduct an elicitation study using data and visual design probes to examine if and how experts with a spectrum of ML expertise use semantic interactions to update a simple classification model.
Optimal Subsampling with Influence Functions
Subsampling is a common and often effective method to deal with the computational challenges of large datasets.
Optimal Sub-sampling with Influence Functions
Sub-sampling is a common and often effective method to deal with the computational challenges of large datasets.
A Tutorial on Bayesian Optimization of Expensive Cost Functions, with Application to Active User Modeling and Hierarchical Reinforcement Learning
We present a tutorial on Bayesian optimization, a method of finding the maximum of expensive cost functions.
Bayesian Optimization
Hierarchical Reinforcement Learning
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