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  • Data Science

Highlights of the 2018 Joint Statistical Meetings

Two Sigma researchers provide an overview of some of the most interesting lectures and sessions at JSM 2018, and highlight some of the most important challenges statisticians face going forward.

  • Technology

Sundial: Harmonizing Concurrency Control and Caching in a Distributed OLTP Database Management System

Distributed transactions suffer from poor performance due to two major limiting factors. First, distributed transactions suffer from high latency because each of their accesses to remote data incurs a long network delay. Second, this high latency increases the likelihood of contention among distributed transactions, leading to high abort rates and low performance. The authors present Sundial, an in-memory distributed optimistic concurrency control protocol that addresses these two limitations.

  • Data Science
  • Markets & Economy

Making Sense of the Sharpe Ratio

Two Sigma’s Labs team recently performed an in-depth survey of the extensive literature on the Sharpe ratio and published its findings in a new Technical Report.

  • Data Science

Learning and Memorization

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.