202 citations · 638 across the 18 of their papers we have counts for
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3 papers · 1 filter
stat.ML2017★ 202 cited
Generalization in Deep Learning
Kenji Kawaguchi, Leslie Pack Kaelbling, Yoshua Bengio
This paper provides theoretical insights into why and how deep learning can generalize well, despite its large capacity, complexity, possible algorithmic instability, nonrobustness…
cs.LG2017★ 2 cited
Deep Semi-Random Features for Nonlinear Function Approximation
Kenji Kawaguchi, Bo Xie, Vikas Verma +1
We propose semi-random features for nonlinear function approximation. The flexibility of semi-random feature lies between the fully adjustable units in deep learning and the random…
cs.LG2017★ 72 cited
Depth Creates No Bad Local Minima
Haihao Lu, Kenji Kawaguchi
In deep learning, \textit{depth}, as well as \textit{nonlinearity}, create non-convex loss surfaces. Then, does depth alone create bad local minima? In this paper, we prove that wi…