Machine Learning and Statistics

State-of-the-art machine learning/AI systems consist of complex pipelines with choices of hyperparameters, models and configuration details that need to be tuned for optimal performance. The AutoML project develops automated methods for optimizing AI pipelines, making AI development more broadly accessible.…

成立: 2016年12月5日

ALICE Automated Learning and Intelligence for Causation and Economics Alice is a project to direct Artificial Intelligence towards economic decision making. We are building tools that combine state-of-the-art machine learning with econometrics – the measurement of economic systems -- in…

End-to-end guide design for CRISPR/Cas9 with machine learning Azimuth and Elevation: On-target and off-target guide prediction The CRISPR/Cas9 system provides state-of-the art genome editing capabilities. However, several facets of this system are under investigation for further characterization and optimization. One…

Water managers in the western United States rely on long-term forecasts of temperature and precipitation to prepare for droughts and other wet weather extremes. To improve the accuracy of these long-term forecasts, the U.S. Bureau of Reclamation (USBR) and the…

EconML is an open source Python package developed by the ALICE team at Microsoft Research that applies the power of machine learning techniques to estimate individualized causal responses from observational or experimental data. The suite of estimation methods provided in EconML…

Machine Learning for Cancer Immunotherapy Microsoft Research is contributing our Artificial Intelligence and Machine Learning expertise towards important research questions at the intersection of cancer and the immune system. Cancer is the second leading cause of death in the United States.…

Microsoft Research New England aims to build the accessibility systems of the future. In particular, we are focused on building systems to better support sign language users and low-vision readers. Accessibility is a major concern for many people with disabilities.…

This project develops techniques that enable AI to use computing infrastructure more efficiently. The goals are to maintain predictive accuracy while reducing carbon emissions, whether embodied in manufactured hardware, or produced from electricity usage when green energy is not available.