11 citations · 14 across the 5 of their papers we have counts for
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stat.ML2020★ 11 cited
Generalisation Guarantees for Continual Learning with Orthogonal Gradient Descent
Mehdi Abbana Bennani, Thang Doan, Masashi Sugiyama
In Continual Learning settings, deep neural networks are prone to Catastrophic Forgetting. Orthogonal Gradient Descent was proposed to tackle the challenge. However, no theoretical…
stat.ML2020★ 2 cited
-ABC: Outlier-Robust Approximate Bayesian Computation Based on a Robust Divergence Estimator
Masahiro Fujisawa, Takeshi Teshima, Issei Sato +1
Approximate Bayesian computation (ABC) is a likelihood-free inference method that has been employed in various applications. However, ABC can be sensitive to outliers if a data dis…