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Two Sigma is proud to sponsor NeurIPS 2018, which brings together top researchers in deep learning, neural nets, and other areas of machine learning.

Launched in 1987, the annual Conference on Neural Information Processing Systems (NeurIPS) is among the world’s foremost conferences on machine learning. With roots in computational neuroscience, NeurIPS has become a crucial gathering for researchers to share insights and innovations in deep learning, neural networks, and more.

Two Sigma has sponsored NeurIPS since 2010, with numerous Two Sigma researchers attending (click here for an overview of standout papers, talks, presentations, and workshops from 2017). We are proud once again to be sponsoring the conference in 2018, to be held in Montreal, Canada.

Here’s how to find the Two Sigma career fair booth at the 2018 NeurIPS Conference!

Two Sigma Talks & Poster Sessions Schedule

Tuesday, December 4th

Poster Session: Gradient Sparsification for Communication-Efficient Distributed Optimization

  • Presenter: Jialei Wang
  • Time: 10:45am
  • Location: Room 210 & 230 AB #158

Thursday, December 6th

Spotlight Session: Graph Oracle Models, Lower Bounds, and Gaps for Parallel Stochastic Optimization

  • Presenter: Jialei Wang
  • Time: 04:20pm
  • Location: Room 517 CD

Poster Session: Graph Oracle Models, Lower Bounds, and Gaps for Parallel Stochastic Optimization

  • Presenter: Jialei Wang
  • Time: 05:00pm
  • Location: Room 210 & 230 AB #11

Poster Session: Sparse PCA from Sparse Linear Regression

  • Presenter: Madalina Persu
  • Time: 05:00pm
  • Location: Room 210 & 230 AB #66

Saturday, December 8th

Interpretability and Robustness in Audio, Speech, and Language Workshop

  • Invited Speaker: Mike Schuster
  • Time: 03:30pm
  • Location: Room 513DEF

Research Papers

Calling all techies, scientists, problem solvers and programmers. We’re hiring.

Quantitative Researcher in Machine Learning

As a Quantitative Machine Learning Researcher, you will use a rigorous scientific method to develop sophisticated trading models, apply machine learning to vast often esoteric datasets, and partner with engineers to test complex investment hypotheses.

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Research Scientist in AI

As a Research Scientist in AI, you will apply general machine learning and specifically deep learning techniques to many types of problems, but particularly those with large amounts of noisy data. As part of this team you’ll remain connected to the broader research community.

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Software Engineer in Machine Learning

As a Software Engineer in Machine Learning, you will help develop the next generation of our machine learning infrastructure. We’ve attracted engineers who possess special capabilities in a wide variety of domains in-cluding data transformation and visualization, performance optimization, cloud computing, and distributed systems.

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Read some of our Insights