Fundamental Limits of Online and Distributed Algorithms for Statistical Learning and Estimation

NeurIPS 2014 Ohad Shamir

Many machine learning approaches are characterized by information constraints on how they interact with the training data. These include memory and sequential access constraints (e.g. fast first-order methods to solve stochastic optimization problems); communication constraints (e.g. distributed learning); partial access to the underlying data (e.g. missing features and multi-armed bandits) and more... (read more)

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