Machine learning (ML) systems are rapidly increasing in size, are acquiring new capabilities, and are increasingly deployed in high-stakes settings. As with other powerful technologies, safety for ML should be a leading research priority. In response to e…

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The rapid progress in deep reinforcement learning (RL) over the last few years holds the promise of fixing the shortcomings of computer opponents in video games and of unlocking entirely new region…

In this piece, the Friendly Overfitting Argument is laid out, as well as when it doesn’t hold. Is overfitting in Machine Learning and Artificial Intelligence really as bad as people make it out to be?

The rapid progress in deep reinforcement learning (RL) over the last few years holds the promise of fixing the shortcomings of computer opponents in video games and of unlocking entirely new region…

This monograph aims at providing an introduction to key concepts, algorithms, and theoretical results in machine learning. The treatment concentrates on probabilistic models for supervised and unsupervised learning problems. It introduces fundamental conc…

Amazon Advertising helps companies build their brand and connect with shoppers, through ads shown both within and beyond Amazon’s store, including websites, apps, and streaming TV content in more than 15 countries. Businesses or brands of all sizes includ…

We present an environment, benchmark, and deep learning driven automated theorem prover for higher-order logic. Higher-order interactive theorem provers enable the formalization of arbitrary mathematical theories and thereby present an interesting, open-e…

Why this is the first rule, some baseline heuristics, and when to move on to machine learning.