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Found 5 papers, 0 papers with code
Learning Interpretable Heuristics for WalkSAT
The performance of these algorithms crucially depends on heuristics for setting noise parameters and scoring variables.
Lockout: Sparse Regularization of Neural Networks
Many regression and classification procedures fit a parameterized function $f(x;w)$ of predictor variables $x$ to data $\{x_{i}, y_{i}\}_1^N$ based on some loss criterion $L(y, f)$.
Targeted transfer learning to improve performance in small medical physics datasets
The growing use of Machine Learning has produced significant advances in many fields.
Conditional Super Learner
In this article we consider the Conditional Super Learner (CSL), an algorithm which selects the best model candidate from a library conditional on the covariates.
ContamiNet: Detecting Contamination in Municipal Solid Waste
Leveraging over 30, 000 images each with up to 89 labels collected by Recology---an integrated resource recovery company with both residential and commercial trash, recycling and composting services---the authors develop ContamiNet, a convolutional neural network, to identify contaminating material in residential recycling and compost bins.
