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Trace-norm regularization is a widely-used and successful approach for collaborative filtering and matrix completion. However, its theoretical understanding is surprisingly weak,... Watch Video
Most online algorithms used in machine learning today are based on variants of mirror descent or follow-the-leader. In this paper, we present an online algorithm based on a completely... Watch Video
Learning from Experts and Multi-armed Bandits are two of the most common settings studied in online learning. Whereas the first setting assumes that the performance of all k actions... Watch Video
After a classifier is trained using a machine learning algorithm and put to use in a real world system, it often faces noise which did not appear in the training data. Particularly... Watch Video
The problem of stochastic convex optimization with bandit feedback (in the learning community) or without knowledge of gradients (in the optimization community) has received much... Watch Video
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