38 citations · 73 across the 9 of their papers we have counts for
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cs.LG2020
Homeomorphic-Invariance of EM: Non-Asymptotic Convergence in KL Divergence for Exponential Families via Mirror Descent
Frederik Kunstner, Raunak Kumar, Mark Schmidt
Expectation maximization (EM) is the default algorithm for fitting probabilistic models with missing or latent variables, yet we lack a full understanding of its non-asymptotic con…
cs.LG2020★ 2 cited
Adaptive Gradient Methods Converge Faster with Over-Parameterization (but you should do a line-search)
Sharan Vaswani, Issam Laradji, Frederik Kunstner +3
Adaptive gradient methods are typically used for training over-parameterized models. To better understand their behaviour, we study a simplistic setting -- smooth, convex losses wi…