Bayesian Active Learning for Classification and Preference Learning
Just Sort It! A Simple and Effective Approach to Active Preference Learning
The Analysis of Sequential Experiments with Feedback to Subjects
Information-Based Objective Functions for Active Data Selection
Stochastic Batch Acquisition: A Simple Baseline for Deep Active Learning
The Power of Ensembles for Active Learning in Image Classification
Active Learning for Convolutional Neural Networks: A Core-Set Approach
Bad Students Make Great Teachers: Active Learning Accelerates Large-Scale Visual Understanding
Exploring Bayesian Optimization: Breaking Bayesian Optimization into small, sizeable chunks
An Experimental Design Perspective on Model-Based Reinforcement Learning
Multi-Stage Bean Machine Visualization: Advantages of Repeated Optimization