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Found 3 papers, 1 papers with code
A Unified Batch Selection Policy for Active Metric Learning
To avoid redundancy between triplets, our method collectively selects batches with maximum joint entropy, which simultaneously captures both informativeness and diversity.
Enhancing Haptic Distinguishability of Surface Materials with Boosting Technique
Discriminative features are crucial for several learning applications, such as object detection and classification.
Batch Decorrelation for Active Metric Learning
We present an active learning strategy for training parametric models of distance metrics, given triplet-based similarity assessments: object $x_i$ is more similar to object $x_j$ than to $x_k$.
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