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cs.LG2026
ORTHOBO: Orthogonal Bayesian Hyperparameter Optimization
Maresa Schröder, Pascal Janetzky, Michael Klar +1
Bayesian optimization is widely used for hyperparameter optimization when model evaluations are expensive; however, noisy acquisition estimates can lead to unstable decisions. We i…
cs.LG2019★ 16 cited
Robust Learning Under Label Noise With Iterative Noise-Filtering
Duc Tam Nguyen, Thi-Phuong-Nhung Ngo, Zhongyu Lou +3
We consider the problem of training a model under the presence of label noise. Current approaches identify samples with potentially incorrect labels and reduce their influence on t…