1 citations · 1 across the 8 of their papers we have counts for
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Generalized Distribution-Free Semi-Supervised Learning with Risk Rewrite
Yushi Hirose, Hiroo Irobe, Takafumi Kanamori
Typical semi-supervised learning (SSL) methods rely on distributional assumptions, and their performance degrades when these are violated. While PNU learning, a risk rewriting meth…
Distributional Spectral Diagnostics for Localizing Grokking Transitions
Ziyue Wang, Yufeng Ying, Takafumi Kanamori
In grokking, a model first fits the training data while test accuracy remains low, and only later begins to generalize. We ask whether this transition can be localized from observe…
Robust VAEs via Generating Process of Noise Augmented Data
Hiroo Irobe, Wataru Aoki, Kimihiro Yamazaki +5
Advancing defensive mechanisms against adversarial attacks in generative models is a critical research topic in machine learning. Our study focuses on a specific type of generative…