In the machine learning research community, it is generally believed that there is a tension between memorization and generalization. This paper examines the extent to which this tension exists, by exploring whether it is possible to generalize by memorizing alone.
Two Sigma researchers share highlights from NIPS 2017.
An overview of best practices derived from building a machine-learning based starter bot for Halite, Two Sigma's public artificial intelligence programming challenge.
A senior Two Sigma researcher provides an overview of some of the most interesting Deep Learning research from ICML 2017.
Two Sigma Co-founder and Co-chairman David Siegel offers his views on these topics and more at Bloomberg’s Sooner Than You Think conference.
An overview of Rademacher Averages, a fundamental concept from statistical learning theory that can be used to derive uniform sample-dependent bounds to the deviation of samples averages from their expectations.
Two Sigma researchers discuss notable advances in deep learning, optimization algorithms, Bayesian techniques, and time-series analysis presented at 2016's Conference on Neural Information Processing Systems (NIPS).
A presentation on fundamental questions in algorithmic data science, a discipline at the border of computer science and statistics.
A Two Sigma research scientist provides an overview of some of the most interesting research presented at ICML 2016.