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cs.LG2024
ADOPT: Modified Adam Can Converge with Any with the Optimal Rate
Shohei Taniguchi, Keno Harada, Gouki Minegishi +7
Adam is one of the most popular optimization algorithms in deep learning. However, it is known that Adam does not converge in theory unless choosing a hyperparameter, i.e., ,…
cs.LG2024
Unsupervised Outlier Detection using Random Subspace and Subsampling Ensembles of Dirichlet Process Mixtures
Dongwook Kim, Juyeon Park, Hee Cheol Chung +1
Probabilistic mixture models are recognized as effective tools for unsupervised outlier detection owing to their interpretability and global characteristics. Among these, Dirichlet…