174 citations · 991 across the 46 of their papers we have counts for
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cs.LG2018★ 1 cited
Size-Noise Tradeoffs in Generative Networks
Bolton Bailey, Matus Telgarsky
This paper investigates the ability of generative networks to convert their input noise distributions into other distributions. Firstly, we demonstrate a construction that allows R…
cs.LG2018★ 103 cited
Gradient descent aligns the layers of deep linear networks
Ziwei Ji, Matus Telgarsky
This paper establishes risk convergence and asymptotic weight matrix alignment --- a form of implicit regularization --- of gradient flow and gradient descent when applied to deep…
cs.LG2018★ 64 cited
Risk and parameter convergence of logistic regression
Ziwei Ji, Matus Telgarsky
Gradient descent, when applied to the task of logistic regression, outputs iterates which are biased to follow a unique ray defined by the data. The direction of this ray is the ma…