1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.LG2002★ 1 cited
Approximating Incomplete Kernel Matrices by the em Algorithm
Koji Tsuda, Shotaro Akaho, Kiyoshi Asai
In biological data, it is often the case that observed data are available only for a subset of samples. When a kernel matrix is derived from such data, we have to leave the entries…
cs.AI2002
Maximing the Margin in the Input Space
Shotaro Akaho
We propose a novel criterion for support vector machine learning: maximizing the margin in the input space, not in the feature (Hilbert) space. This criterion is a discriminative v…