Sample Variance Penalization

Most of the time, supervised machine learning is done by optimizing the average loss on the training set, i.e. empirical risk minimization, perhaps with a (usually not data-dependent) regularization term added in. However, there was a nice paper a couple of years back by Maurer and Pontil introducing Sample Variance Penalization. The basic idea is to optimize a combination of…
Original post: Sample Variance Penalization
Source: Machined Learnings

CNTK and Vowpal Wabbit tutorials at NIPS

CNTK and Vowpal Wabbit tutorials at NIPS Both CNTK and Vowpal Wabbit have pirate tutorials at NIPS. The CNTK tutorial is 1 hour during the lunch break of the Optimization workshop while the VW tutorial is 1 hour during the lunch break of the Extreme Multiclass workshop. Consider dropping by either if interested. CNTK is a deep learning system started…
Original post: CNTK and Vowpal Wabbit tutorials at NIPS
Source: Machine Learning (Theory)

How to get a job at Google — as a data scientist

by SEAN GERRISHIf you are a regular at this blog, thanks for reading. We will continue to bring you posts from the range of data science activities at Google. This post is different. It is for those who are interested enough in our activities to consider joining us. We briefly highlight some of the things we look for in data…
Original post: How to get a job at Google — as a data scientist
Source: Unofficial Google Data Science

Using Empirical Bayes to approximate posteriors for large "black box" estimators

by OMKAR MURALIDHARANMany machine learning applications have some kind of regression at their core, so understanding large-scale regression systems is important. But doing this can be hard, for reasons not typically encountered in problems with smaller or less critical regression systems. In this post, we describe the challenges posed by one problem — how to get approximate posteriors — and…
Original post: Using Empirical Bayes to approximate posteriors for large "black box" estimators
Source: Unofficial Google Data Science