DS-MLR: Exploiting Double Separability for Scaling up Distributed Multinomial Logistic Regression

arXiv: Learning, Volume abs/1604.04706, 2016.

Cited by: 9|Views78
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Abstract:

Scaling multinomial logistic regression to datasets with very large number of data points and classes has not been trivial. This is primarily because one needs to compute the log-partition function on every data point. This makes distributing the computation hard. In this paper, we present a distributed stochastic gradient descent based o...More

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