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Log-linear models are a far-reaching extension of logistic regression, while con- ditional random fields (CRFs) are a special case of log-linear models suitable for so-called structured learning tasks. Structured learning means learning to predict outputs that have internal structure. For example, r ...

This talk will discuss examples of how Amazon applies machine learning to large-scale data, and open research questions inspired by these applications. One important question is how to distinguish between users that can be influenced, versus those who are merely likely to respond. Another question i ...

We propose to solve the link prediction problem in graphs using a supervised matrix factorization approach. The model learns latent features from the topological structure of a (possibly directed) graph, and is shown to make better predictions than popular unsupervised scores. We show how these late ...