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Found 4 papers, 0 papers with code
Representation Costs of Linear Neural Networks: Analysis and Design
For different parameterizations (mappings from parameters to predictors), we study the regularization cost in predictor space induced by $l_2$ regularization on the parameters (weights).
MaxiMin Active Learning in Overparameterized Model Classes}
Generating labeled training datasets has become a major bottleneck in Machine Learning (ML) pipelines.
Regret Bounds and Regimes of Optimality for User-User and Item-Item Collaborative Filtering
We assume that the matrix encoding the preferences of each user type for each item type is randomly generated; in this way, the model captures structure in both the item and user spaces, the amount of structure depending on the number of each of the types.
Learning a Tree-Structured Ising Model in Order to Make Predictions
We study the problem of learning a tree Ising model from samples such that subsequent predictions made using the model are accurate.
