16 citations · 33 across the 3 of their papers we have counts for
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cs.LG2020★ 7 cited
Amazon SageMaker Autopilot: a white box AutoML solution at scale
Piali Das, Valerio Perrone, Nikita Ivkin +22
AutoML systems provide a black-box solution to machine learning problems by selecting the right way of processing features, choosing an algorithm and tuning the hyperparameters of…
cs.LG2020
Amazon SageMaker Automatic Model Tuning: Scalable Gradient-Free Optimization
Valerio Perrone, Huibin Shen, Aida Zolic +12
Tuning complex machine learning systems is challenging. Machine learning typically requires to set hyperparameters, be it regularization, architecture, or optimization parameters,…
cs.LG2016
Convexification of Learning from Constraints
Iaroslav Shcherbatyi, Bjoern Andres
Regularized empirical risk minimization with constrained labels (in contrast to fixed labels) is a remarkably general abstraction of learning. For common loss and regularization fu…